Method and system for improving biomarker based disease assessments

Abstract

The present invention relates to the field of diagnostics. In particular, it relates to a computer-implemented method for assessing a medical condition in a subject comprising the steps of determining the amount of at least one biomarker of interest for said medical condition in a sample of the subject, comparing the determined amount of the at least one biomarker to a reference, and assessing the medical condition in the subject based on the comparison and improving the reliability of the said assessment by integrating at least one clinical parameter value of the medical condition obtained from a dataset of continuously determined clinical parameter values comprising the said at least one clinical parameter value into the biomarker-based assessment, wherein the sample and the at least one clinical parameter value have been obtained from the subject within a short time window, wherein said at least one biomarker is determined continuously by using a point-of-care analytical device and / or wherein the dataset comprising the at least one clinical parameter is determined by a wearable sensing device. Moreover, the invention provides a system and a device for assessing a medical condition in a subject as well as the use of the amount of at least one biomarker of interest for said medical condition in a sample of the subject or a detection agent therefor for assessing a medical condition in said subject.

Description

[0001] Method and system for improving biomarker based disease assessments

[0002] The present invention relates to the field of diagnostics. In particular, it relates to a computer- implemented method for assessing a medical condition in a subject comprising the steps of determining the amount of at least one biomarker of interest for said medical condition in a sample of the subject, comparing the determined amount of the at least one biomarker to a reference, and assessing the medical condition in the subject based on the comparison and improving the reliability of the said assessment by integrating at least one clinical parameter value of the medical condition obtained from a dataset of continuously determined clinical parameter values comprising the said at least one clinical parameter value into the biomarkerbased assessment, wherein the sample and the at least one clinical parameter value have been obtained from the subject within a short time window, wherein said at least one biomarker is determined by using a point-of-care analytical device and / or wherein the dataset comprising the at least one clinical parameter is continuously determined by a wearable sensing device.. Moreover, the invention provides a system and a device for assessing a medical condition in a subject as well as the use of the amount of at least one biomarker of interest for said medical condition in a sample of the subject or a detection agent therefor for assessing a medical condition in said subject.

[0003] A low-cost point of care (POC) in vitro diagnostic (IVD) device for detection of biomarkers is the key for frequent monitoring of patients at the comfort of their homes. Some solutions for remote patient monitoring of heart failure patients have been reported previously. However, these solutions rely either only on digital wearables (smart watch, chest patch, garment, etc.) or ambulatory or implantable devices (electrocardiogram (ECG), blood pressure monitor, intracardiac pressure measurement, continuous glucose monitoring systems, etc.). Some solutions rely on a combination of results from digital wearables and hospital lab blood testing.

[0004] E.g., for case of heart failure patients who are discharged early from hospitals, a highly reliable low-cost POC IVD system for detection of biomarkers, such as NT-proBNP, is of utmost importance. Such type of POC IVD device can be used for periodic and frequent monitoring of heart failure patients and can help in reducing the rate of re-hospitalizations and deaths. POC IVD systems can typically easily handled, are of small size, are stable at room temperature, require low blood volume, and have low turnaround times. However, based on the current state of the art such low-cost handheld POC IVD devices lack accuracy, precession range, and measurement range of a centralized lab-test. None of the existing solutions addresses the unmet need of a highly reliable low-cost POC IVD system for detection of NT-proBNP for patient self-testing that has lab-like performance.

[0005] US 11,615,891 B2 mentions testing of patients for heart failure events using data from sensors or other sources, such as NT-proBNP testing. The individual results are used to determine heart failure events. Based on the said heart failure events that may be within or outside an alert state, assessments of the patients may be made. The document is not concerned with the improvement of biomarker-based diagnostics.

[0006] US 8,602,996 B2 discloses the use of device-based sensors and bedside biomarker assays to detect worsening heart failure. However, the disclosed methods are based on monitoring heart failure based on sensor data with less specificity. Once heart failure worsening is suspected to occur, the patient will be reevaluated using the highly specific biomarker assay. The sensor data are not integrated in order to improve biomarker based testing.

[0007] US20140031643A1 relates to cardiac assessments based on various different parameters. Besides physiological sensor circuits, such as heart sound sensor or a respiration sensor, physiological sensors for generating a signal of heart failure biomarker, such as NT-proBNP or BNP, are mentioned. The document is not concerned with the improvement of biomarker-based diagnostics.

[0008] The technical problem underlying the invention may be seen as the provision of means and methods for complying with the aforementioned needs. The technical problem is solved by the embodiments characterized in the claims and herein below.

[0009] Thus, the present invention relates to a method for assessing a medical condition in a subject comprising the steps of: a) determining the amount of at least one biomarker of interest for said medical condition in a sample of the subject; b) comparing the determined amount of the at least one biomarker to a reference; c) assessing the medical condition in the subject based on the comparison made in step b); and d) improving the reliability of the assessment made in step c) by integrating at least one clinical parameter of the medical condition obtained from a dataset comprising the said at least one clinical parameter into the biomarker-based assessment of step c), wherein the sample and the dataset comprising the at least one clinical parameter have been obtained from the subject within a short time window.

[0010] In particular, steps c) and d) may be carried out together, i.e. as step c) assessing the medical condition in the subject based on the comparison made in step b) and improving the reliability of the said assessment by integrating at least one clinical parameter value of the medical condition obtained from a dataset of continuously determined clinical parameter values comprising the said at least one clinical parameter value into the biomarker-based assessment, wherein the sample and the at least one clinical parameter value have been obtained from the subject within a short time window.

[0011] Thus, contemplated is also a computer-implemented method for assessing a medical condition in a subject comprising the steps of: a) determining the amount of at least one biomarker of interest for said medical condition in a sample of the subject; b) comparing the determined amount of the at least one biomarker to a reference; and c) assessing the medical condition in the subject based on the comparison made in step b) and improving the reliability of the said assessment by integrating at least one clinical parameter value of the medical condition obtained from a dataset of continuously determined clinical parameter values comprising the said at least one clinical parameter value into the biomarker-based assessment, wherein the sample and the at least one clinical parameter value have been obtained from the subject within a short time window, wherein said at least one biomarker is determined by using a point-of-care analytical device and / or wherein the dataset comprising the at least one clinical parameter is continuously determined by a wearable sensing device.

[0012] As used in the following, the terms “have”, “comprise” or “include” are meant to have a nonlimiting meaning or a limiting meaning. Thus, having a limiting meaning, these terms may refer to a situation in which besides the feature introduced by these terms no other features are present in an embodiment described, i.e. the terms have a limiting meaning in the sense of “consisting of’ or “essentially consisting of’. Having a non-limiting meaning, the terms refer to a situation where besides the feature introduced by these terms one or more other features are present in an embodiment described. Further, as used in the following, the terms “preferably”, “more preferably”, “most preferably”, "particularly", "more particularly", “most particularly”, “typically”, “more typically”, and “most typically” are used in conjunction with features in order to indicate that these features are preferred, but not mandatory features. Thus, the terms shall indicate that the recited features are pivotally envisaged in accordance with the invention but alternative features may yet also be envisaged.

[0013] Further, it will be understood that the term “at least one” as used herein means that one or more of the items referred to following the term may be used in accordance with the invention. For example, if the term indicates that at least one item shall be used this may be understood as one item or more than one item, i.e. two, three, four, five or any other number. Depending on the item the term refers to the skilled person understands as to what upper limit the term may refer, if any.

[0014] The method as referred to in accordance with the present invention includes a method which essentially consists of the aforementioned steps or a method which includes further steps. Moreover, the method of the present invention, preferably, is an ex vivo method, i.e. not practiced on the human or animal body, and, more preferably, an in vitro method. Moreover, it may comprise steps in addition to those explicitly mentioned above. For example, further steps may relate to the determination of further markers and / or to sample pre-treatments or evaluation of the results obtained by the method. The method may be carried out manually or assisted by automation. Preferably, step (a), (b), (c) and / or (d) may in total or in part be assisted by automation, e.g., by a suitable robotic and sensory equipment for the determination in step (a) or by using a data processing device as specified elsewhere herein for any one or all of steps (b) to (d). Preferably, the method of the invention is a computer implemented method.

[0015] The term “assessing” as used herein refers to (i) diagnosing the presence or absence of a medical condition referred to herein, (ii) staging of a medical condition referred to herein, (iii) differentiating a medical condition referred to herein from another medical condition, (iv) predicting the occurrence of a medical condition referred to herein in a given predictive time window, (v) monitoring the development of a medical condition referred to herein, (vi) identifying a subject which shall be subjected to further diagnostics measures for diagnosing the medical condition referred to herein, and / or (vii) identifying a subject as being susceptible for a therapy against a medical condition referred to herein. Diagnosing as mentioned herein refers to determine whether the subject suffers from the medical condition, or not. Staging a medical condition means determining the stage, grade or severity of the medical condition. Differentiating as meant herein refers to distinguishing the medical condition from other disease or conditions exhibiting similar or identical symptoms. Predicting the occurrence of the medical condition refers to determining the likelihood with which the subject will develop the medical condition within a predictive time window. Monitoring as mentioned herein refers to determining the presence or absence of the medical condition at least two different time points. Identifying a subject which shall be subjected to further diagnostics measures for diagnosing the medical condition means that it may be assessed whether further diagnostic measures shall be applied to the subject, or not. Identifying a subject as being susceptible for a therapy against a medical condition means that it is assessed whether a certain therapy against the medical condition is beneficial for the subject, or not, i.e. cure or ameliorates the medical condition or symptoms thereof.

[0016] As will be understood by those skilled in the art, the assessment of the present invention is usually not intended to be correct for 100% of the subjects to be tested. However, the term requires that a correct assessment (such as the diagnosis, differentiation, prediction, identification or assessment of a therapy as referred to herein) can be made for a relevant portion of subjects within a given cohort and, preferably, for a statistically significant portion of subjects within a given cohort. Whether a portion is statistically significant can be determined without further ado by the person skilled in the art using various well-known statistic evaluation tools, e.g., determination of confidence intervals, p-value determination, Student's t-test, Mann- Whitney test etc. Details may be found in Dowdy and Wearden, Statistics for Research, John Wiley & Sons, New York 1983. Preferred confidence intervals are at least 90%, at least 95%, at least 97%, at least 98%, or at least 99%. The p-values are, preferably, 0.4, 0.1, 0.05, 0.01, 0.005, or 0.0001.

[0017] The term “medical condition” as used herein refers to a disease or pathological condition in a subject which is accompanied by a change in the amount of at least one biomarker that can be determined in a sample of a subject as specified elsewhere herein and by a change of at least one clinical parameter in a dataset that can be obtained from said subject as specified elsewhere herein. The medical condition in accordance with the present invention may affect any tissue or organ of the subject. Typically, a medical condition may affect the cardiovascular system including the heart, the neuronal system, the gastrointestinal system, the kidney, the hematopoietic system, or connective tissue.

[0018] Preferably, the medical condition may be a cardiovascular disease or disorder, preferably, myocardial infarction, heart failure, thrombosis, pulmonary embolism, clotting disorders, or atherosclerosis. Also preferably, the medical condition may be a neuronal disease or disorder, preferably, neurodegenerative diseases, more preferably, Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, brain injury, stroke or multiple sclerosis. Preferably, the medical condition may be a metabolic disease or disorder, preferably, metabolic syndrome, diabetes, insulin resistance, dyslipidemia, hepatic disorders, hepatitis, non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH). Further, the medical condition may be, preferably, cancer, preferably, prostate cancer, ovarian cancer, pancreatic cancer, colorectal cancer, breast cancer or hepatic cancer.

[0019] The “subject” as referred to herein is, preferably, a mammal. Mammals include, but are not limited to, domesticated animals (e.g., cows, sheep, cats, dogs, and horses), primates (e.g., humans and non-human primates such as monkeys), rabbits, and rodents (e.g., mice and rats). Preferably, the subject is a human subject. Preferably, the subject to be tested is of any age. The subject to be tested, preferably, shall suffer from or suspected to suffer from the medical condition.

[0020] The term “sample” as used herein refers to any body fluid or tissue sample from the subject to be investigated. It is to be understood that the sample will depend on the biomarker to be determined. Preferably, said sample is a body fluid sample, preferably, a blood sample ( e.g., whole blood, serum or plasma), a saliva sample, a cerebrospinal fluid sample, a urine sample, a tissue sample, an interstitial fluid sample or a sweat sample. The skilled artisan is well aware of how such samples can be obtained from the subject. In accordance with the method of the present invention, it is, preferably, envisaged that the sample is obtained and analyzed by a point-of-care analyzing device as specified elsewhere herein.

[0021] Preferably, the sample in accordance with the present invention has been obtained from the subject at a predefined time. Typically, samples may be taken at the same day times, e.g. in the morning, noon, afternoon or evening, before or after eating, exercise, sleeping, etc. In particular, if the method of the invention is applied for monitoring the development of a medical condition referred to herein, it is to be understood that samples need to be taken at different time points. Those time points shall be comparable to each other with respect to the physiological stage of the subject, e.g. at the same day times, e.g. in the morning, noon, afternoon or evening, before or after eating, exercise, sleeping, etc.. Predefined timing of sample taking helps to standardize the samples and to minimize the influence of environmental factors such as circadian rhythmic, dietary factors and the like. The timing and frequency may be predefined by an attending physician based on the medical condition and the individual needs of a subject. Preferably, the sample in accordance with the present invention may be obtained at least once, twice or three times a day, preferably, at a predefined time point. Sample taking at predefined time points may be automated by using a point-of-care analytical device, preferably, a wearable point-of-care analytical device such as a in vivo senor patch.

[0022] The term “amount” as used herein refers to the absolute amount of the biomarker, the relative amount or concentration of the biomarker as well as any value or parameter, which correlates thereto or can be derived therefrom. Such values or parameters comprise intensity signal values from all specific physical or chemical properties obtained from the said biomarker or a detection agent and / or detectable label. The values or parameters can be obtained by direct or indirect measurement. Direct measuring relates to measuring the amount or concentration of the biomarker based on a signal which is obtained from the biomarker molecule itself and the intensity of which directly correlates with the number of molecules of the biomarker present in the sample. Such a signal - sometimes referred to herein as intensity signal - may be obtained, e.g., by measuring an intensity value of a specific physical or chemical property of the biomarker molecule. Indirect measuring includes measuring of a signal obtained from a secondary component, i.e. a component not being the biomarker molecule itself. It is to be understood that values correlating to the aforementioned amounts or parameters can also be obtained and / or modified by all standard mathematical operations.

[0023] Determining the amount in the method of the present invention may be carried out by any technique, which allows for detecting the presence or absence or the amount of said biomarker. Suitable techniques depend on the molecular nature and the properties of the biomarkers. The skilled artisan is well aware of those differences in the measurable properties. Moreover, it will be understood that a biomarker may be, preferably, detected by using detection agents. The skilled artisan is, however, also well aware of said different detection agents and / or techniques. Preferably, the amount of the biomarker according to the invention is determined by using a point-of-care analytical device or by a continuous monitoring in-vivo sensor as described elsewhere herein.

[0024] In accordance with the present invention, determining the amount of a biomarker can be achieved by all known means for determining such amounts in a sample. Said means comprise immunoassay devices and methods, which may utilize labelled molecules in various sandwich, competition, or other immunoassay formats. Said assays will develop a signal, which is indicative for the presence or absence of the protein. Moreover, the signal strength can, preferably, be correlated directly or indirectly (e.g. reverse- proportional) to the amount of the biomarker present in a sample. Further suitable methods comprise measuring a physical or chemical property specific for the biomarkers.

[0025] Preferably, the biomarker can be determined by using a detection agent, which specifically binds to the biomarker and which binding can be detected. A “detection agent” refers in this context to any molecule that is capable of specifically binding to the biomarker to be detected. The detection agent is selected based on the type of analysis to be conducted. Detection agents include but are not limited to aptamers, antibodies, adnectins, ankyrins, antibody mimetics and other protein scaffolds, small molecules, nucleic acids, lectins, affybodies, nanobodies, avimers, and peptidomimetics. Preferably, such a detection agent may be an antibody or an antigen-binding fragment thereof. An “antibody” in accordance with the present invention may encompass all types of antibodies, which specifically bind to the biomarker protein. Preferably, the antibody of the present invention is a monoclonal antibody, a polyclonal antibody, a single chain antibody, a chimeric antibody or any fragment or derivative of such antibodies being still capable of binding to the biomarker protein specifically. An antigen binding fragment refers to one or more fragments of an antibody that retain the ability to specifically bind to an antigen. Examples of binding fragments encompassed within the term “antigen binding fragment” include a fragment antigen binding (Fab) fragment, a Fab’ fragment, a F(ab’)2 fragment, a heavy chain antibody, a singledomain antibody (sdAb), a single-chain fragment variable (scFv), a fragment variable (Fv), a VH domain, a VL domain, a single domain antibody, a nanobody, an IgNAR (immunoglobulin new antigen receptor), a di-scFv, a bispecific T-cell engager (BITEs), a dual affinity re-targeting (DART) molecule, a triple body, a diabody, a single-chain diabody, an alternative scaffold protein, and a fusion protein thereof. Specific binding as used in the context of the antibody of the present invention means that the antibody does not cross react with other molecules present in the sample to be investigated. Specific binding can be tested by various well-known techniques. Antibodies or fragments thereof, in general, can be obtained by using methods, which are described in standard text books, e.g., in Harlow and Lane "Antibodies, A Laboratory Manual", CSH Press, Cold Spring Harbor, 1988. Monoclonal antibodies can be prepared by the techniques, which comprise the fusion of mouse myeloma cells to spleen cells derived from immunized mammals and, preferably, immunized mice. Preferably, an immunogenic peptide is applied to a mammal. The said peptide is, preferably, conjugated to a carrier protein, such as bovine serum albumin, thyroglobulin, and keyhole limpet hemocyanin (KLH). Depending on the host species, various adjuvants can be used to increase the immunological response. Such adjuvants encompass, preferably, Freund’s adjuvant, mineral gels, e.g., aluminum hydroxide, and surface-active substances, e.g., lysolecithin, pluronic polyols, polyanions, peptides, oil emulsions, keyhole limpet hemocyanin, and dinitrophenol. Monoclonal antibodies, which specifically bind to an analyte can be subsequently prepared using the well-known hybridoma technique, the human B cell hybridoma technique, and the EBV hybridoma technique. Detection systems using antibodies are based on the highly specific binding affinity of antibodies for a specific antigen, i.e. the biomarker protein. Binding events result in a physicochemical change that can be detected as described elsewhere herein.

[0026] An “adnectin” as used herein, refers to a synthetic binding protein, also known as monobody, based on the 10th fibronectin type III (10Fn3) domain. It is a member of the immunoglobulin superfamily and contains a “beta sandwich” protein fold that bears striking resemblance to an antibody domain. As such, adnectins represent a simple and robust alternative to antibodies for creating target-binding proteins. A major advantage of adnectins over conventional antibodies is that adnectins can readily be used as genetically encoded intracellular inhibitors, that is one can express an adnectin inhibitor in a cell of choice by simply transfecting the cell with an adnectin expression vector. Preferably, the adnectin as used herein, shall bind specifically to a biomarker as specified elsewhere herein.

[0027] An “ankyrin” as used herein, refers to a family of proteins that comprise binding sites for a wide range of membrane proteins. Ankyrins contain four functional domains: (i) an N-terminal domain with 24 tandem ankyrin repeats that are responsible for the recognition of multiple membrane proteins, (ii) a central domain that binds to spectrin, (iii) a death domain that binds to proteins involved in apoptosis, and (iv) a C-terminal regulatory domain that is highly variable between different anykrin proteins. Ankyrins are encoded in humans by three genes, which in turn produce multiple proteins through alternative splicing. Preferably, the ankyrins as used herein, shall bind specifically to at least one biomarker described herein elsewhere.

[0028] “Antibody mimetics” as used herein, refer to compounds, which can specifically bind antigens, similar to an antibody, but are not structurally related to antibodies. Usually, antibody mimetics are artificial peptides or proteins with a molar mass of about 3 to 20 kDa, which comprise one, two or more exposed domains specifically binding to an antigen. Examples include inter alia the LACI-Dl (lipoprotein-associated coagulation inhibitor); affilins, e.g. human-y B crystalline or human ubiquitin; cystatin; Sac7D from Sulfolobus acidocaldarius; lipocalin and anticalins derived from lipocalins; DARPins (designed ankyrin repeat domains); SH3 domain of Fyn; Kunits domain of protease inhibitors; monobodies, e.g. the 10th type III domain of fibronectin; adnectins: knottins (cysteine knot miniproteins); atrimers; evibodies, e.g. CTLA4-based binders, affibodies, e.g. three-helix bundle from Z-domain of protein A from Staphylococcus aureus; Trans-bodies, e.g. human transferrin; tetranectins, e.g. monomeric or trimeric human C-type lectin domain; microbodies, e.g. trypsin-inhibitor-II; affilins; armadillo repeat proteins. Nucleic acids and small molecules are sometimes considered antibody mimetics as well (aptamers), but not artificial antibodies, antibody fragments and fusion proteins composed from these. Common advantages over antibodies are better solubility, tissue penetration, stability towards heat and enzymes, and comparatively low production costs. Preferably, the antibody mimetics as used herein, shall bind specifically to at least one biomarker described herein elsewhere.

[0029] A “scaffold protein” as used herein, refers to a specific protein whose main function is to mediate protein complexes. Scaffold proteins usually have multiple protein domains that mediate binding to other proteins. Examples of scaffold proteins include but are not limited to the protein inaD from rhabdomeres of Drosophila melanogaster or titin, a protein found in muscles. A “lectin” as used herein, refers to carbohydrate-binding proteins that are highly specific for sugar groups. They occur ubiquitously in nature and may bind to soluble carbohydrates or carbohydrate moieties that are part of a glycoprotein or glycolipid. Lectins typically agglutinate certain cells and / or precipitate glycoconjugates. As such, they find use in medicine, particularly for blood typing. Lectins are also used in neuroscience for anterograde labelling to trace the path of efferent axons. Preferably, the lectin as used herein, shall bind specifically to at least one biomarker as described herein elsewhere.

[0030] An “affibody” as used herein are small, highly robust proteins with high affinity to target proteins. In contrast to antibodies, affibodies are composed of alpha helices and lack disulphide bridges. In particular, they are based on a three-helix bundle domain with 58 amino acids and have a molar mass of about 6 kDa. They can be expressed in soluble and proteolytically stable forms in various host cells on its own or via fusion with other protein partners. Affibodies can be used for protein purification, enzyme inhibition, research reagents for protein capture and detection, diagnostic imaging, and targeted therapy. For example, the second generation affibody, ABY-025 binds selectively to HER2 receptors with picomolar affinity. Preferably, the affibodies as used herein, shall bind specifically to at least one biomarker described herein elsewhere.

[0031] A “nanobody” as used herein, refers to tiny, recombinantly produced antigen binding fragments, typically consisting of a single monomeric variable antibody domain. Although nanobodies lack the light chains and heavy chain constant domain, the antigen-binding capacity remains similar to that of conventional antibodies. Typically, the complementarity-determining region 3 (CDR3) of nanobodies is similar or even longer than that of human variable domain of the heavy immunoglobulin chain (VH). They can form finger-like structures to recognize cavities or hidden epitopes that are not available to monoclonal antibodies, a feature that enhances the binding affinity and specificity of nanobodies. Preferably, the nanobodies as used herein, shall bind specifically to at least one biomarker described herein elsewhere.

[0032] An “avimer” (short of avidity multimer) as used herein, refers to artificial proteins with multiple binding sites for specific binding to certain antigens. They are not structurally related to antibodies and thus, are classified as antibody mimetics. Typically, they consist of two or more peptide sequences of 30 to 35 amino acids, connected by linker peptides. The individual sequences are derived from A domains of various membrane receptors and have a rigid structure, stabilised by disulfide bonds and calcium. Each A domain can bind to a certain epitope of the target protein. The combination of domains binding to different epitopes of the same protein increases affinity to this protein, an effect known as avidity. Avimers are widely used in early detection in tissue imaging, treatment, and study on carcinogenesis. Preferably, the avimers as used herein, shall bind specifically to at least one biomarker described herein elsewhere.

[0033] A “peptidomimetic” as used herein, refers to compound that mimics one or more structural aspects or biological activities of a naturally-occurring polypeptide, but which comprises one or more non-peptide or non-naturally occurring chemical structures or bonds. Peptidomimetics are frequently used to mimic the biological action of a peptide, thus they may be small proteinlike chain designed to mimic one or more peptides. Peptidomimetics are often synthesized based on existing peptides of interest with one or more modifications to alter the molecule's structure or properties. Modifications can change the peptide molecule's stability, half-life, biological activity, absorption, or side-effects (e.g., toxicity, solubility, hydrophobicity, sidechain charge, or flexibility) of a peptide. Peptidomimetics can be useful as medicaments or drug-like compounds developed rationally, or based on modification of an existing peptide with known or putative biological activity. Preferably, the peptidomimetics as used herein, shall bind specifically to at least one biomarker described herein elsewhere.

[0034] Typically, a detection agent to be used in accordance with the present invention for determining at least one biomarker shall comprise a detectable label. A “detectable label” as referred to herein, which may be used in accordance with the invention include gold particles, latex beads, acridan ester, luminol, ruthenium, enzymatically active labels, radioactive labels, magnetic labels, e.g., magnetic beads, including paramagnetic and superparamagnetic labels, and fluorescent labels. Enzymatically active labels include e.g. horseradish peroxidase, alkaline phosphatase, beta-Galactosidase, Luciferase, and derivatives thereof. Suitable substrates for detection include di-amino-benzidine (DAB), 3,3'-5,5'-tetramethylbenzidine, NBT-BCIP (4- nitro blue tetrazolium chloride and 5-bromo-4-chloro-3-indolyl-phosphate. A suitable enzymesubstrate combination may result in a coloured reaction product, fluorescence or chemiluminescence, which can be measured according to methods known in the art (e.g. using a light-sensitive film or a suitable camera system). As for measuring the enzymatic reaction, the criteria given above apply analogously. Typical fluorescent labels include e.g. fluorescent proteins (such as GFP and its derivatives), Cy3, Cy5, Texas Red, Fluorescein, the Alexa dyes, brilliant violet or brilliant ultraviolet. Also, the use of quantum dots as fluorescent labels is contemplated. Typical radioactive labels include 35S, 1251, 32P, 33P, and the like. A radioactive label can be detected by any method known and appropriate, e.g. a light-sensitive film or a phosphor imager. Suitable labels may also be or comprise tags, such as biotin, digoxygenin, His-, GST-, FLAG-, GFP-, MYC-tag, influenza A virus hemagglutinin (HA), maltose binding protein, and the like.

[0035] The amount of a biomarker can be detected using a biomarker / detection agent complex. The amount may also be detected indirectly from the biomarker / detection agent complex, for example, as a result of a reaction that is subsequent to the biomarker / detection agent interaction, but is dependent on the formation of the biomarker / detection agent complex. In some examples, the amount of a biomarker may be detected directly from the biomarker in a biological sample. The amounts of biomarkers can also be detected using a multiplexed format that allows for the simultaneous detection of two or more biomarkers in a biological sample. In the multiplexed format, binding molecules may be immobilized, directly or indirectly, covalently or non- covalently, in discrete locations on a solid support.

[0036] The determined amounts of the biomarkers are compared to a reference in accordance with the method of the present invention. The term “reference” as used herein relates to an amount or value, which allows for allocation of a subject into either a group of subjects suffering from a medical condition, or a group of subjects, which do not suffer from said medical condition. Such a reference can be a threshold amount, which separates these groups from each other. Accordingly, the reference shall be an amount, which allows for allocation of a subject into a group of subjects suffering from a disease or condition or being at risk for developing it, or not. A suitable threshold amount separating the two groups can be calculated without further ado by the statistical tests referred to herein elsewhere based on amounts of biomarkers from either a subject or group of subjects known to suffer from a medical condition or a subject or group of subjects known not to suffer from a medical condition. The reference amount applicable for an individual subject may vary depending on various physiological parameters such as age, gender, or subpopulation.

[0037] Reference amounts can, in principle, be calculated for a cohort of subjects based on the average or mean values for a given parameter such as biomarker amount by applying standard statistically methods. In particular, accuracy of a test such as a method aiming to diagnose an event, or not, is best described by its receiver-operating characteristics (ROC). The ROC graph is a plot of all of the sensitivity / specificity pairs resulting from continuously varying the decision threshold over the entire range of data observed. The clinical performance of a diagnostic method depends on its accuracy, i.e. its ability to correctly allocate subjects to a certain assessment. The ROC plot indicates the overlap between the two distributions by plotting the sensitivity versus 1 -specificity for the complete range of thresholds suitable for making a distinction. On the y-axis is sensitivity, or the true-positive fraction, which is defined as the ratio of number of true-positive test results to the product of number of true-positive and number of false-negative test results. This has also been referred to as positivity in the presence of a disease or condition. It is calculated solely from the affected subgroup. On the x-axis is the false-positive fraction, or 1 -specificity, which is defined as the ratio of number of false-positive results to the product of number of true-negative and number of false-positive results. It is an index of specificity and is calculated entirely from the unaffected subgroup. Because the true- and false-positive fractions are calculated entirely separately, by using the test results from two different subgroups, the ROC plot is independent of the prevalence of the event in the cohort. Each point on the ROC plot represents a sensitivity / - specificity pair corresponding to a particular decision threshold. A test with perfect discrimination (no overlap in the two distributions of results) has an ROC plot that passes through the upper left corner, where the true-positive fraction is 1.0, or 100% (perfect sensitivity), and the false-positive fraction is 0 (perfect specificity). The theoretical plot for a test with no discrimination (identical distributions of results for the two groups) is a 45° diagonal line from the lower left corner to the upper right comer. Most plots fall in between these two extremes. If the ROC plot falls completely below the 45° diagonal, this is easily remedied by reversing the criterion for "positivity" from "greater than" to "less than" or vice versa. Qualitatively, the closer the plot is to the upper left corner, the higher the overall accuracy of the test. Dependent on a desired confidence interval, a threshold can be derived from the ROC curve allowing for the diagnosis or prediction for a given event with a proper balance of sensitivity and specificity, respectively. Accordingly, the reference to be used for the aforementioned method of the present invention, i.e. a threshold, which allows to discriminate between subjects suffering from a medical condition and those who do not suffer therefrom can be generated, usually, by establishing a ROC for said cohort as described above and deriving a threshold amount therefrom. Dependent on a desired sensitivity and specificity for an assessment method, the ROC plot allows deriving suitable thresholds. It will be understood that an optimal sensitivity is desired for excluding a subject for being at increased risk (i.e. a rule out) whereas an optimal specificity is envisaged for a subject to be assessed as being at an increased risk (i.e. a rule in).

[0038] The term “comparing” as used herein encompasses comparing the determined amount for a biomarker as referred to herein to a reference. It is to be understood that comparing as used herein refers to any kind of comparison made between the values for the amount with the reference. However, it is to be understood that, preferably, identical types of values are compared with each other, e.g., if an absolute amount is determined and to be compared in the method of the invention, the reference shall also be an absolute amount, if a relative amount is determined and to be compared in the method of the invention, the reference shall also be a relative amount, etc. The comparison may be carried out manually or computer assisted. The value of the amount and the reference can be, e.g., compared to each other and the said comparison can be automatically carried out by a computer program executing an algorithm for the comparison. The computer program carrying out the said evaluation will provide the desired assessment in a suitable output format.

[0039] As used here, “improving the reliability” signifies a notable, typically, significant, increase in the reliability of the assessment. This means the test results will be more comparable to those produced by comprehensive laboratory methods, rather than assessments based solely on biomarkers, such as those derived from a Point-of-Care (POC) IVD test. The term “integrating” as used herein refers to any technique that combines the biomarkerbased assessment and a further assessment based on a clinical parameter as referred to herein. Integrating may be made in accordance with the method of the present invention by confirming or disconfirming one assessment using the other. This may include, preferably, by weighting the different assessments, e.g., by allocating scores to the assessments and integrated by combining the different scores in a scoring system. In addition, computer-implemented algorithms may be used for integration, typically, correlation analyses, regression analyses, hypothesis testing, and / or time series analysis. The skilled artisan is well aware of how to implement such algorithms in a computer using suitable computer program code. Preferably, said integrating the at least one further clinical parameter value obtained from the dataset into the biomarker-based assessment comprises i) comparing the at least one clinical parameter value to a reference and assessing the subject based on the said comparison, and ii) comparing the assessment of the subject based on the at least one clinical parameter value of step i) to the biomarker-based assessment. The assessment is preferably more reliable when the clinical parameter-based evaluation (from step i) confirms the findings of the biomarker-based assessment (from step d), ideally being essentially identical. Should there be discrepancies, the established correlation between the biomarkers and the selected clinical parameter can then be leveraged to bridge the gap between POC IVD test results and full laboratory accuracy.

[0040] The term “clinical parameter” as referred to herein encompasses any physiological parameter that can be determined from the subject, preferably, in a non-invasive measure by using wearable sensing devices. The clinical parameter shall be associated with the medical condition, i.e. it shall change between a subject suffering from the medical condition and a subject not suffering from the medical condition. Preferably, the at least one clinical parameter is selected from the group consisting of blood pressure, heart rate, electro cardiogram data, body mass index (BMI), smoking status, and alcohol consumption status, saturated blood oxygen, ankle or wrist swelling parameters (e.g. circumference and / or tissue elasticity of respective body parts and / or bioimpedance parameters and / or hydration level), respiration rate, stroke volume, heart rate variability, cognitive assessment, activity, six minute walking distance, motor function, gait and balance function, sensory function, reflex function, visual function, hearing, mood and behavior, electroencephalography, thoracic impedance, echocardiography, micro-motion of heart, cardiac output, sleep function, blood glucose data, tissue image data, ultrasound data and the like. A clinical parameter in accordance with the invention can also be a parameter derived from any of the aforementioned clinical parameters, such as a value of the clinical parameter or a trend or tendency of change that can be derived from two or more values for any one of the aforementioned clinical parameters. Preferably, the at least one clinical parameter value(s) comprised in the dataset have in accordance with the present invention been monitored continuously, at predefined time points during a predefined interval or on demand, preferably, at the time of sample taking.

[0041] The term “dataset” as used herein refers to one or more data obtained from the subject reflecting the at least one clinical parameter. Thus, typically, the dataset comprises values for the at least one clinical parameter obtained at one or more time points. Preferably, the said time points are simultaneous or in close temporal proximity to the time point when the sample for the biomarker determination has been taken, i.e. the sample and the dataset comprising the at least one clinical parameter shall be obtained from the subject within a short time window. The dataset may comprise only data for one clinical parameter, e.g. it may comprise only values for the heart rate of the subject at different time points. Yet, the dataset may also comprise data of different clinical parameters, e.g., it may comprise values for the heart rate as well as the heart pressure. Preferably, the said dataset comprising the at least one clinical parameter is determined by a wearable sensing device. Preferably, the values for the at least one clinical parameter comprised by the dataset are continuously determined, preferably, by a wearable sensing device as defined elsewhere herein.

[0042] References for the at least one clinical parameter can be provided as described above for biomarkers. Similarly, comparison of the at least one clinical parameter to the reference can also be done as described for biomarkers elsewhere herein.

[0043] Continuous determination of the at least one clinical parameter as referred to herein also allows, in addition to individual changes of the values of at least one clinical parameter, for analyzing changes, patterns and / or correlations of different clinical parameters with a predefined time window, being or comprising the short time window referred to herein. To this end, automated algorithms can be implemented on a computer used to assist carrying out the method of the invention. These algorithms, typically, comprise correlation analyses, regression analyses, hypothesis testing, and / or time series analysis. The skilled artisan is well aware of how to implement such algorithms in a computer using suitable computer program code. Preferably, those algorithms may be used to enable autocorrelation analysis. Correlation and pattern appearance between different clinical parameters, preferably, heart rate, blood pressure, oxygen saturation, and respiration rate, is less pronounced or structured, less predictable or more disorganized in a subject suffering from a medical condition such as heart failure compared to a control subject not suffering from said medical condition. The same applies to the correlation and pattern appearance between different clinical parameters between two time points of measurements in subjects suffering from a medical condition such as heart failure compared to a subject not suffering from said medical condition. An autocorrelation analysis indicating less autocorrelation values is, thus, also indicative for the presence of the medical condition or its severity. When a biomarker, such as NT-proBNP, is determined at time t, autocorrelation analysis for two or more clinical parameter values selected from the group consisting of heart rate, blood pressure, oxygen saturation, respiration rate and / or heart rate variability, may be performed at various time lags. Typically, those time lags may be t vs t-30 min, t vs t-1 hour, t vs t-2 hours, t vs t-4 hours up to t vs t-24 hours, wherein the last biomarker amount was determined at t-24 hours. For consistent high autocorrelation values, true biomarker (t-24) value > or = true biomarker (t) amount, and for consistent low autocorrelation values, true biomarker (t-24) value < true biomarker (t) amount. A measurement is considered free from discrepency if the autocorrelation values of the clinical parameters within the time windows from t to t-24h are consistent with the biomarker amounts determined at both, t and t-24h. The autocorrelation values in other words can estimate the amount of NT-proBNP. Should there be discrepancies between the estimated values of the NT-proBNP with the clinical parameters and the value of NT-proBNP obtained from POC IVD tests, the established correlation between the biomarkers and the selected clinical parameter can then be leveraged to bridge the gap between POC IVD test results and full laboratory accuracy.

[0044] Thus, preferably, the method of the present invention comprises carrying out steps a) and b) at a first predefined time point and at a second predefined time point and wherein step c) of the method comprises assessing the medical condition in the subject based on the comparison made in step b) for the amounts of the first time point and the second time point as well as the at least one clinical parameter value of the medical condition obtained from a dataset of continuously determined clinical parameter values at the said first time point and the said second time point. More preferably, said method further comprises an autocorrelation analysis in step c).

[0045] The term “within a short time window” as used means that the time point of sample taking and the time point of determining the at least one clinical parameter shall be in close temporal proximity. It will be understood that a suitable time window depends on the medical condition to be assessed, the kind of assessment envisaged, the biomarker to be determined and the clinical parameter to be determined. Typically, a short time window in accordance with the invention may be a time window of at most 1 day, at most 12 hours, at most 6 hours, at most 3 hours, at most 2 hours, at most 1 hour, at most 30 minutes, at most 15 minutes, at most 10 minutes, at most 5 minutes, at most 2 minutes, at most 1 minute, at most 30 seconds, at most 20 seconds, at most 10 seconds or at most 5 seconds. Preferably, the term within a short time window also encompasses simultaneously determining the clinical parameter and taking the sample.

[0046] In order to safeguard that the sample for biomarker determination and the clinical parameter comprised in the dataset are determined in close temporal proximity, i.e. within a short time window as specified above, said at least one biomarker is determined, preferably, by using a point-of-care analytical device and the dataset comprising the at least one clinical parameter is, preferably, determined by a wearable sensing device.

[0047] Advantageously, it has been found in accordance with the present invention that the reliability of a biomarker-based assessment of a medical condition can be increased by integrating one or more clinical parameters for the medical condition from a dataset comprising said parameter(s). The sample for the biomarker-based assessment and the dataset comprising the clinical parameter shall be obtained from the subject within a short time window. Biomarker-based assessment of a medical condition may sometimes yield ambiguous results, which may give rise to false positive or false negative assessments.

[0048] For example, if a measured amount for a cardiac biomarker, such as NT-proBNP, is close to a threshold value for a cardiovascular medical condition such as heart failure, e.g., the investigated subject cannot be diagnosed reliably as suffering from heart failure, or not. This particularly holds true for patient-self testing approaches using point-of-care in vitro diagnostic Assays. However, by integrating a clinical parameter-based assessment of the medical condition, which is based on clinical parameter values at about the time of sample taking in the biomarker-based assessment, the reliability of a patient-self tested biomarker-based assessment can be significantly improved and assessment result can be more comparable to an assessment made with an professional use POC test or a centralized lab test. Clinical parameters such as heart rate, blood pressure, oxygen saturation, ankle swelling, breathing rate, general activity or sleeping pattern will further strengthen the biomarker-based assessment in that the determined value for the clinical parameter either confirms, e.g., the diagnosis of heart failure, or disconfirms the said diagnosis.

[0049] The definitions of the terms and explanations made before apply mutatis mutandis to the following embodiments of the invention.

[0050] In a preferred embodiment of the method of the present invention, said biomarker is a biomarker for a cardiovascular disease or disorder. Preferably, said biomarker is selected from the group consisting of a cardiac troponin, preferably, Troponin I or T, Creatine kinase MB (CK-MB), a Brain natriuretic peptides, preferably, NT-proBNP, myoglobin, C-reactive protein (CRP), D- dimer, Fibrinogen and Lipoprotein associated phospholipase 2 (LP-PLA2). Moreover, the at least one clinical parameter in said case is, preferably, selected from the group consisting of: blood pressure, heart rate, electro cardiogram data, body mass index (BMI), smoking status, and alcohol consumption status, saturated blood oxygen, ankle or wrist swelling parameters (e.g. circumference and / or tissue elasticity of respective body parts), respiration rate, stroke volume, heart rate variability.

[0051] Cardiac troponin refers to a complex of three regulatory proteins (troponin C, troponin I and troponin T) that are integral to muscle contraction in cardiac muscle. Cardiac troponins, in particular, troponin I and T are widely used as diagnostic and prognostic indicators for myocardial infarction, acute coronary syndrome, stroke, etc. The preferred troponin biomarkers of the present invention are troponin I or troponin T.

[0052] The term “troponin I” (TNNI3) as used herein, refers to an inhibitory subunit of troponin encoded in humans by the TNNI3 gene. It is one of the three subunits that form the troponin complex in the thin filaments of striated muscle. The Tnl subfamily contains three genes: Tnl- skeletal-fast-twitch, Tnl-skeletal-slow-twitch, and Tnl-cardiac. This gene encodes the Tnl- cardiac protein and is exclusively expressed in cardiac muscle tissues. Troponin I is useful in making a diagnosis of heart failure, and of ischemic heart disease. For troponin I, there are three isoforms known in humans (UniProt accession numbers A0A590UJN1, K7EJP0 and K7EN02). Several orthologues of troponin I have been reported in various animal species.

[0053] The troponin I protein referred to in accordance with the present invention is, preferably, human troponin I having an amino acid sequence as deposited under UniProt accession number P19429. It will be understood that the term “troponin I” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned troponin I protein. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human troponin I protein, preferably over the entire length of the said troponin I proteins, respectively.

[0054] The term “troponin T” (TNNT2) as used herein, refers to an inhibitory subunit of troponin encoded in humans by the TNNT2 gene. The encoded protein is the tropomyosin-binding subunit of the troponin complex, which is located on the thin filament of striated muscles and regulates muscle contraction in response to alterations in intracellular calcium ion concentration. Mutations in this gene have been associated with familial hypertrophic cardiomyopathy as well as with dilated cardiomyopathy. For troponin T, there are twelve isoforms known in humans (UniProt accession numbers P45379-1 to P45379-12). Several orthologues of troponin T have been reported in various animal species.

[0055] The troponin T protein referred to in accordance with the present invention is, preferably, human troponin T having an amino acid sequence as deposited under UniProt accession number P45379. It will be understood that the term “troponin T” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned troponin T protein. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human troponin T protein, preferably over the entire length of the said troponin T proteins, respectively.

[0056] The term “CKB” as used herein, refers to the creatine kinase B-type (brain-type) encoded in humans by the CKB gene. The protein encoded by this gene is a cytoplasmic enzyme involved in energy homeostasis. The encoded protein reversibly catalyzes the transfer of phosphate between ATP and various phosphogens such as creatine phosphate. For CKB, there are seven potential isoforms known in humans (UniProt accession numbers A0A0S2Z471, H0YJG0, H0YJJ7, H0YJK0, G3V461, G3V4N7 and G3V2I1). Several orthologues of CKB have been reported in various animal species.

[0057] The CKB protein referred to in accordance with the present invention is, preferably, human CKB having an amino acid sequence as deposited under UniProt accession number P12277. It will be understood that the term “CKB” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned CKB protein. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human CKB protein, preferably over the entire length of the said CKB proteins, respectively.

[0058] The term “CKM” as used herein, refers to the creatine kinase muscle encoded in humans by the CKM gene. The protein encoded by this gene is a cytoplasmic enzyme involved in cellular energy homeostasis. The encoded protein reversibly catalyzes the transfer of "energy-rich" phosphate between ATP and creatine and between phosphocreatine and ADP. Its functional entity is a MM-CK homodimer in striated skeletal and cardiac muscle. Several orthologues of CKM have been reported in various animal species.

[0059] The CKM protein referred to in accordance with the present invention is, preferably, human CKM having an amino acid sequence as deposited under UniProt accession number P06732. It will be understood that the term “CKM” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned CKM protein. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human CKM protein, preferably over the entire length of the said CKM proteins, respectively.

[0060] Brain natriuretic peptides (BNP), also known as B-type natriuretic peptides, refer to hormones secreted by cardiomyocytes in the heart ventricles in response to stretching caused by increased ventricular blood volume. The 32-amino acid polypeptide BNP is secreted attached to a 76- amino acid N-terminal fragment in the prohormone called NT-proBNP, which is biologically inactive. Once released, BNP binds to and activates the atrial natriuretic factor receptor NPRA, and to a lesser extent NPRB. BNP is involved in the decrease of systemic vascular resistance and central venous pressure as well as in the increase in natriuresis. The preferred BNP of the present invention is NT-proBNP.

[0061] The term “NT-proBNP” refers to the N-terminal prohormone of brain natriuretic peptide encoded in humans by the NPPB gene. NT-proBNP is a cardiac hormone that plays a key role in mediating cardio-renal homeostasis and may function as a paracrine antifibrotic factor in the heart. It is also involved Involved in regulating the extracellular fluid volume and maintaining the fluid-electrolyte balance through natriuresis, diuresis, vasorelaxation, and inhibition of renin and aldosterone secretion. NT-proBNP is a prohormone with a 76 amino acid N-terminal inactive protein that is cleaved from the molecule to release brain natriuretic peptide 32. Several orthologues of NT-proBNP have been reported in various animal species.

[0062] The NT-proBNP protein referred to in accordance with the present invention is, preferably, human NT-proBNP having an amino acid sequence as deposited under UniProt accession number P16860. It will be understood that the term “NT-proBNP” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned NT-proBNP protein. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human NT-proBNP protein, preferably over the entire length of the said NT-proBNP proteins, respectively.

[0063] The term “myoglobin” as used herein, refers to monomeric heme protein encoded in humans by the MB gene. This gene encodes a member of the globin superfamily and is predominantly expressed in skeletal and cardiac muscles. The encoded protein forms a monomeric globular hemoprotein that is primarily responsible for the storage and facilitated transfer of oxygen from the cell membrane to the mitochondria. This protein also plays a role in regulating physiological levels of nitric oxide. For myoglobin, there are five potential isoforms known in humans (UniProt accession numbers Q8WVH6, B0QYF7, B0QYF8, F2Z2F1 and F2Z337). Several orthologues of myoglobin have been reported in various animal species.

[0064] The myoglobin protein referred to in accordance with the present invention is, preferably, human myoglobin having an amino acid sequence as deposited under UniProt accession number P02144. It will be understood that the term “myoglobin” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned myoglobin protein. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human myoglobin protein, preferably over the entire length of the said myoglobin proteins, respectively.

[0065] The term “CRP” as used herein, refers to the C-reactive protein encoded in humans by the CRP gene. The protein encoded by this gene belongs to the pentraxin family, which also includes serum amyloid P component protein and pentraxin 3. Pentraxins are involved in complement activation and amplification via communication with complement initiation pattern recognition molecules, but also complement regulation via recruitment of complement regulators. For CRP, there are two isoforms known in humans (UniProt accession numbers P02741-1 and P02741- 2). Several orthologues of myoglobin have been reported in various animal species. The C-reactive protein referred to in accordance with the present invention is, preferably, human CRP having an amino acid sequence as deposited under UniProt accession number P02741. It will be understood that the term “CRP” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned C-reactive protein. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human C-reactive protein, preferably over the entire length of the said C-reactive proteins, respectively.

[0066] The term “D-dimer” as used herein, refers to a dimer that is a fibrin degradation product, a small protein fragment present in the blood after a blood clot is degraded by fibrinolysis. It contains two D fragments of the fibrin protein joined by a cross-link, hence forming a protein dimer. D- dimers are used in the diagnosis of thrombotic disorders, such as venous thromboembolism, as well as predictive biomarkers for blood disorder disseminated intravascular coagulation.

[0067] The D-dimer protein referred to in accordance with the present invention is, preferably, human D-dimer having an amino acid sequence as deposited under RCSB PDB accession number 3H32. It will be understood that the term “D-dimer” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned D-dimer protein. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human D-dimer protein, preferably over the entire length of the said D-dimer proteins, respectively.

[0068] The term “fibrinogen” as used herein, refers to a glycoprotein complex, produced in the liver. It is composed of two trimers, with each trimer composed of three different polypeptide chains, the fibrinogen alpha chain (also termed the Aa or a chain) encoded by the FGA gene, the fibrinogen beta chain (also termed the Bp or p chain) encoded by the FGB gene, and the fibrinogen gamma chain (also termed the y chain) encoded by the FGG gene. All three genes are located on the long or "q" arm of human chromosome. During tissue and vascular injury, it is converted enzymatically by thrombin to fibrin and then to a fibrin-based blood clot, which occludes blood vessels to stop bleeding. For fibrinogen alpha chain, there are two isoforms known in humans (UniProt accession numbers P02671-1 and P02671-2). For fibrinogen beta chain, there are also two isoforms known in humans (UniProt accession numbers D6REL8 and F8W6P4). For fibrinogen gamma chain, there are also two isoforms known in humans (UniProt accession numbers P02679-1 and P02679-2). Several orthologues of fibrinogen alpha, beta and gamma chain respectively, have been reported in various animal species.

[0069] The fibrinogen protein referred to in accordance with the present invention is, preferably, human fibrinogen having an amino acid sequence as deposited under UniProt accession number P02671 (fibrinogen alpha chain), P02675 (fibrinogen beta chain) and P02679 (fibrinogen gamma chain). It will be understood that the term “fibrinogen” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned fibrinogen protein. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human fibrinogen protein, preferably over the entire length of the said fibrinogen, respectively.

[0070] The term “LP-PLA2” as used herein, refers to the lipoprotein associated phospholipase 2 encoded in humans by the PLA2G7 gene. The protein encoded by this gene is a secreted enzyme that catalyzes the degradation of platelet-activating factor to biologically inactive products. Defects in this gene are a cause of platelet-activating factor acetylhydrolase deficiency. Several orthologues of LP-PLA2 have been reported in various animal species.

[0071] The LP-PLA2 protein referred to in accordance with the present invention is, preferably, human LP-PLA2 having an amino acid sequence as deposited under UniProt accession number QI 3093. It will be understood that the term “LP-PLA2” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned LP-PLA2. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human LP-PLA2 protein, preferably over the entire length of the said LP-PLA2, respectively.

[0072] In another preferred embodiment of the method of the present invention, said biomarker is a biomarker for a neuronal disease or disorder. Preferably, said biomarker is selected from the group consisting of Tau protein, beta-amyloid protein, Neurofilament protein, Glial fibrillary acidic protein (GFAP), Ubiquitin C-terminal hydrolase LI, SI 00 Calcium binding protein B, alpha Synuclein, Neuron-specific enolase, and Myelin basic protein (MBP). Moreover, the at least one clinical parameter in said case is, preferably, is selected from the group consisting of cognitive assessment, motor function, gait and balance function, sensory function, reflex function, visual function, hearing, mood and behavior, electroencephalography, sleep function.

[0073] The term “tau protein” as used herein, refers to the tubulin associated unit encoded in humans by the MAPT gene. This gene encodes the microtubule-associated protein tau (MAPT) whose transcript undergoes complex, regulated alternative splicing, giving rise to several mRNA species. MAPT transcripts are differentially expressed in the nervous system, depending on stage of neuronal maturation and neuron type. This protein plays a role in maintaining stability of microtubules in axons and might be involved in the establishment and maintenance of neuronal polarity. For the tau protein, there are nine iso forms known in humans (UniProt accession numbers P10636-1 to P10636-9). Several orthologues of the tau protein have been reported in various animal species.

[0074] The tau protein referred to in accordance with the present invention is, preferably, human tau protein having an amino acid sequence as deposited under UniProt accession number P10636. It will be understood that the term “tau protein” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned tau protein. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human tau protein, preferably over the entire length of the said tau proteins, respectively.

[0075] The term “amyloid beta peptide” as used herein, refers to peptides of 36 to 43 amino acids that are the main component of the amyloid plaques found in Alzheimer’s patients. The peptides derive from the amyloid-beta precursor protein (APP), which is cleaved by beta secretase and gamma secretase to yield Ap in a cholesterol-dependent process and substrate presentation.

[0076] The amyloid beta peptide referred to in accordance with the present invention is, preferably, amyloid beta peptide having an amino acid sequence as deposited under Pfam accession number PF03494. It will be understood that the term “amyloid beta peptide” also relates to variants of said peptides. Such variants have at least the same essential biological and immunological properties as the aforementioned amyloid beta peptide. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human amyloid beta peptide, preferably over the entire length of the said amyloid beta peptide, respectively.

[0077] The term “neurofilament protein” as used herein, refers to proteins that belong to the intermediate filament protein family, which is divided into six types based on their gene organization and protein structure. Types I and II are the keratins which are expressed in epithelia. Type III contains the proteins vimentin, desmin, peripherin and glial fibrillary acidic protein (GFAP). Type IV consists of the neurofilament proteins NF-L, NF-M, NF-H and a- internexin. Type V consists of the nuclear lamins, and type VI consists of the protein nestin. Preferred neurofilament proteins of the present invention are the type IV neurofilament proteins NF-L, NF-M and NF-H, which are involved in the maintenance of neuronal caliber. The term “NF-L” refers to the neurofilament light polypeptide encoded in humans by the NEFL gene. The term “NF-H” refers to the neurofilament heavy polypeptide encoded in humans by the NEFH gene. The term “NF-M” refers to the neurofilament medium polypeptide encoded in humans by the NEFM gene. For NF-H, there are two isoforms known in humans (UniProt accession numbers P12036-1 and P12036-2). For NF-M, there are two isoforms known in humans (UniProt accession numbers P07197-1 and P07197-2). Several orthologues of NF-L, NF-M and NF-H have been reported in various animal species.

[0078] The NF-L, NF-M and NF-H proteins referred to in accordance with the present invention are, preferably, human NF-L, NF-M and NF-H proteins having an amino acid sequence as deposited under UniProt accession number P07196 (NF-L), P07197 (NF-M) and P12036 (NF-H). It will be understood that the term “NF-L”, “NF-M” and “NF-H” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned NF-L, NF-M and NF-H proteins. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human NF-L, NF-M and NF-H proteins, preferably over the entire length of the said NF-L, NF-M and NF-H proteins, respectively.

[0079] The term “GFAP” as used herein, refers to the glial fibrillary acidic protein encoded in humans by the GFAP gene. It is a type III intermediate filament (IF) protein that is expressed by numerous cell types of the central nervous system (CNS), including astrocytes and ependymal cells during development. It is involved in many important CNS processes, including cell communication and the functioning of the blood brain barrier. For GFAP, there are three isoforms known in humans (UniProt accession numbers P14136-1 to P14136-3). Several orthologues of GFAP have been reported in various animal species.

[0080] The GFAP referred to in accordance with the present invention is, preferably, human GFAP having an amino acid sequence as deposited under UniProt accession number P14136. It will be understood that the term “GFAP” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned GFAP. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human GFAP, preferably over the entire length of the said GFAP, respectively.

[0081] The term “UCH-L1” as used herein, refers to the ubiquitin carboxy-terminal hydrolase LI encoded in humans by the UCHL1 gene. The protein encoded by this gene belongs to the peptidase C12 family. This enzyme is a thiol protease that hydrolyzes a peptide bond at the C- terminal glycine of ubiquitin. This gene is specifically expressed in the neurons and in cells of the diffuse neuroendocrine system. For UCH-L1, there are five potential isoforms known in humans (UniProt accession numbers D6RJD9, D6RF53, D6RE83, D6R956 and D6R974). Several orthologues of UCH-L1 have been reported in various animal species.

[0082] The UCH-L1 referred to in accordance with the present invention is, preferably, human GFAP having an amino acid sequence as deposited under UniProt accession number P09936. It will be understood that the term “UCH-L1” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned UCH-L1 protein. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human UCH-L1 protein, preferably over the entire length of the said UCH-L1 proteins, respectively.

[0083] The term “S100B” as used herein, refers to the S100 calcium-binding protein B encoded in humans by the S100B gene. The protein encoded by this gene is a member of the SI 00 family of proteins containing 2 EF-hand calcium-binding motifs. S100 proteins are localized in the cytoplasm and / or nucleus of a wide range of cells, and involved in the regulation of a number of cellular processes such as cell cycle progression and differentiation. For SIOOB, there is one potential isoform known in humans (UniProt accession numbers A8MRB1). Several orthologues of SIOOB have been reported in various animal species.

[0084] The SIOOB protein referred to in accordance with the present invention is, preferably, human SIOOB having an amino acid sequence as deposited under UniProt accession number P04271. It will be understood that the term “S100B” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned SIOOB protein. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human SIOOB protein, preferably over the entire length of the said SIOOB proteins, respectively.

[0085] The term “aSyn” as used herein, refers to the protein alpha-synuclein encoded in humans by the SNCA gene. Alpha-synuclein is a member of the synuclein family, which also includes beta- and gamma-synuclein. Synucleins are abundantly expressed in the brain and alpha- and beta- synuclein inhibit phospholipase D2 selectively. aSyn may serve to integrate presynaptic signalling and membrane trafficking. Defects in SNCA have been implicated in the pathogenesis of Parkinson disease. aSyn peptides are a major component of amyloid plaques in the brains of patients with Alzheimer's disease. For aSyn, there are three isoform known in humans (UniProt accession numbers P37840-1 to P37840-3). Several orthologues of aSyn have been reported in various animal species.

[0086] The aSyn protein referred to in accordance with the present invention is, preferably, human aSyn having an amino acid sequence as deposited under UniProt accession number P37840. It will be understood that the term “aSyn” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned aSyn protein. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human aSyn protein, preferably over the entire length of the said aSyn proteins, respectively.

[0087] The term “NSE” as used herein, refers to the neuron specific enolase encoded in humans by the EN02 gene. NSE is one of the three enolase isoenzymes found in mammals. This isoenzyme, a homodimer, is found in mature neurons and cells of neuronal origin. NSE has neurotrophic and neuroprotective properties on a broad spectrum of central nervous system (CNS) neurons, binds in a calcium-dependent manner to cultured neocortical neurons and promotes cell survival. For NSE, there are two isoform known in humans (UniProt accession numbers P09104-1 and P09104-2). Several orthologues of NSE have been reported in various animal species.

[0088] The NSE protein referred to in accordance with the present invention is, preferably, human NSE having an amino acid sequence as deposited under UniProt accession number P09104. It will be understood that the term “NSE” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned NSE protein. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human NSE protein, preferably over the entire length of the said NSE proteins, respectively. The term “MBP” as used herein, refers to the myelin basic protein encoded in humans by the MBP gene. MBP is a major constituent of the myelin sheath of oligodendrocytes and Schwann cells in the nervous system. It is assumed to be important in the process of myelination of nerves in the nervous system. For MBP, there are six isoform known in humans (UniProt accession numbers P02686-1 to P02686-6). Several orthologues of MBP have been reported in various animal species.

[0089] The MBP protein referred to in accordance with the present invention is, preferably, human MBP having an amino acid sequence as deposited under UniProt accession number P02686. It will be understood that the term “MBP” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned MBP protein. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human MBP protein, preferably over the entire length of the said MBP proteins, respectively.

[0090] In yet a preferred embodiment of the method of the present invention, said biomarker is a biomarker for a metabolic disease or disorder. Preferably, said biomarker is selected from the group consisting of Insulin, Glucose Transporter 4 (GLUT4), adiponectin, leptin, Fatty acid binding protein 4, C-peptide, Glycated Hemoglobin (HbAlc), Hepatic Lipase (HL), Alanine Aminotransferase (ALT), and Aspartate Aminotransferase (ASZ). Moreover, the at least one clinical parameter in said case is, preferably, selected from the group consisting of blood pressure, body mass index (BMI), and blood glucose levels.

[0091] The term “insulin” as used herein, refers to a peptide hormone produced by beta cells of the pancreatic islets encoded in humans by the INS gene. It plays a vital role in the regulation of carbohydrate and lipid metabolism. After removal of the precursor signal peptide, proinsulin is post-translationally cleaved into three peptides: the B chain and A chain peptides, which are covalently linked via two disulfide bonds to form insulin, and C-peptide. Binding of insulin to the insulin receptor (IN SR) stimulates glucose uptake. For insulin, there are two iso form known in humans (UniProt accession numbers P01308-1 and P01308-2). Several orthologues of insulin have been reported in various animal species. The insulin protein referred to in accordance with the present invention is, preferably, human insulin having an amino acid sequence as deposited under UniProt accession number P01308. It will be understood that the term “insulin” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned insulin protein. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human insulin protein, preferably over the entire length of the said insulin proteins, respectively.

[0092] The term “GLUT4” as used herein, refers to the glucose transporter type 4 protein encoded in humans by the SLC2A4 gene. GLUT4 is the insulin-regulated glucose transporter found primarily in adipose tissues and striated muscle (skeletal and cardiac). At the cell surface, GLUT4 permits the facilitated diffusion of circulating glucose down its concentration gradient into muscle and fat cells. Once within cells, glucose is rapidly phosphorylated by glucokinase in the liver and hexokinase in other tissues to form glucose-6-phosphate, which then enters glycolysis or is polymerized into glycogen.

[0093] The GLUT4 protein referred to in accordance with the present invention is, preferably, human GLUT4 having an amino acid sequence as deposited under RCSB PDB accession number 7WSN. It will be understood that the term “GLUT4” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned GLUT4 protein. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human GLUT4 protein, preferably over the entire length of the said GLUT4 proteins, respectively.

[0094] The term “AdipoQ” as used herein, refers to the protein hormone and adipokine adiponectin encoded in humans by the ADIPOQ gene. This gene is expressed in adipose tissue exclusively. It encodes a protein with similarity to collagens X and VIII and complement factor Clq. The encoded protein circulates in the plasma and is involved with metabolic and hormonal processes such as regulating glucose levels and fatty acid breakdown. Several orthologues of AdipoQ have been reported in various animal species.

[0095] The AdipoQ protein referred to in accordance with the present invention is, preferably, human AdipoQ having an amino acid sequence as deposited under UniProt accession number QI 5848. It will be understood that the term “AdipoQ” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned AdipoQ protein. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human AdipoQ protein, preferably over the entire length of the said AdipoQ proteins, respectively.

[0096] The term “leptin” as used herein, refers to a protein hormone encoded in humans by the LEP gene. This gene encodes a protein that is secreted by white adipocytes into the circulation and plays a major role in the regulation of energy homeostasis. Circulating leptin binds to the leptin receptor in the brain, which activates downstream signalling pathways that inhibit feeding and promote energy expenditure. This protein also has several endocrine functions, and is involved in the regulation of immune and inflammatory responses, haematopoiesis, angiogenesis, reproduction, bone formation and wound healing. Several orthologues of leptin have been reported in various animal species.

[0097] The leptin protein referred to in accordance with the present invention is, preferably, human insulin having an amino acid sequence as deposited under UniProt accession number P41159. It will be understood that the term “leptin” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned leptin protein. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human leptin protein, preferably over the entire length of the said leptin proteins, respectively. The term “FABP4” as used herein, refers to a carrier protein for fatty acids encoded in humans by the FABP4 gene. FABP4 belongs to a family of small, highly conserved, cytoplasmic proteins that bind long-chain fatty acids and other hydrophobic ligands. It is thought that FABPs roles include fatty acid uptake, transport, and metabolism. It is primarily expressed in adipocytes and macrophages. For FABP4, there is one potential isoform known in humans (UniProt accession numbers E5RIR0). Several orthologues of FABP4 have been reported in various animal species.

[0098] The FABP4 referred to in accordance with the present invention is, preferably, human FABP4 having an amino acid sequence as deposited under UniProt accession number Pl 5090. It will be understood that the term “FABP4” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned FABP4. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human FABP4, preferably over the entire length of the said FABP4, respectively.

[0099] The term “C-peptide” as used herein, refers to a short 31 -amino-acid polypeptide that connects the A-chain of insulin to its B-chain in the proinsulin. C-peptide has been shown to bind to the surface of a number of cell types such as neuronal, endothelial, fibroblast and renal tubular, at nanomolar concentrations to a receptor that is likely G-protein-coupled. The signal activates Ca2+-dependent intracellular signalling pathways such as MAPK, PLCy, and PKC, leading to upregulation of a range of transcription factors. It also has been found to be a bioactive peptide with effects on microvascular blood flow and tissue health. The chemical formula of the C- peptide is C129H211N35O48.

[0100] The term “HbAlc” as used herein, refers to glycated haemoglobin. It is a form of haemoglobin that is chemically linked to a sugar. Most monosaccharides, including glucose, galactose and fructose, spontaneously (i.e. non-enzymatically) bond with haemoglobin when present in the bloodstream. Glycohemoglobin is formed when a ketoamine reaction occurs between glucose and the N-terminal amino acid of the P chain of haemoglobin. HbAlc is measured primarily to determine the three-month average blood sugar level and can be used as a diagnostic test for diabetes mellitus and as an assessment of glycemic control. The HbAlc protein referred to in accordance with the present invention is, preferably, human HbAlc having an amino acid sequence as deposited under RCSB PDB accession number 3B75. It will be understood that the term “HbAlc” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned HbAlc protein. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human HbAlc protein, preferably over the entire length of the said HbAlc proteins, respectively.

[0101] The term “HL” as used herein, refers to the hepatic lipase encoded in humans by the LIPC gene. Hepatic lipase is expressed mainly in liver cells, known as hepatocytes, and endothelial cells of the liver. It enables phospholipase Al activity as well as triglyceride lipase activity and is involved in several processes, including lipid homeostasis, plasma lipoprotein particle remodelling and triglyceride catabolic process. For HL, there are two potential isoform known in humans (UniProt accession numbers E7EUK6 and E7EUJ1). Several orthologues of HL have been reported in various animal species.

[0102] The HL referred to in accordance with the present invention is, preferably, human HL having an amino acid sequence as deposited under UniProt accession number Pl 1150. It will be understood that the term “HL” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned HL. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human HL, preferably over the entire length of the said HL, respectively.

[0103] The term “ALT” as used herein, refers to the alanine aminotransferase (EC 2.6.1.2). ALT is found in plasma and in various body tissues but is most common in the liver. It catalyses the two parts of the alanine cycle. Serum ALT level, serum AST (aspartate transaminase) level, and their ratio (AST / ALT ratio) are routinely measured clinically as biomarkers for liver health. ALT catalyses the transfer of an amino group from L-alanine to a-ketoglutarate, the products of this reversible transamination reaction being pyruvate and L-glutamate as follows: L-alanine + a-ketoglutarate pyruvate + L-glutamate.

[0104] The ALT referred to in accordance with the present invention is, preferably, human ALT having an amino acid sequence as deposited under RCSB PDB accession number 3IHJ. It will be understood that the term “ALT” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned ALT. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human ALT, preferably over the entire length of the said ALT, respectively.

[0105] The term “AST” as used herein, refers to the aspartate aminotransferase (EC 2.6.1.1). It is a pyridoxal phosphate (PLP)-dependent transaminase enzyme that catalyzes the reversible transfer of an a-amino group between aspartate and glutamate and, as such, is an important enzyme in amino acid metabolism. AST is found in the liver, heart, skeletal muscle, kidneys, brain, red blood cells and gall bladder. Serum AST level, serum ALT (alanine transaminase) level, and their ratio (AST / ALT ratio) are commonly measured clinically as biomarkers for liver health. Aspartate transaminase catalyses the interconversion of aspartate and a- ketoglutarate to oxaloacetate and glutamate as follows:

[0106] L- Aspartate (Asp) + a-ketoglutarate oxaloacetate + L-glutamate (Glu)

[0107] The AST referred to in accordance with the present invention is, preferably, human AST having an amino acid sequence as deposited under RCSB PDB accession number 7AAT. It will be understood that the term “AST” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned AST. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human AST, preferably over the entire length of the said AST, respectively.

[0108] In a further preferred embodiment of the method of the present invention, said biomarker is a biomarker for cancer. A cancer biomarker as referred to in accordance with the present invention, typically, is a protein, peptide or small molecule, such as a carbohydrate, which is present in a body fluid or tissue if a subject suffers from cancer or being at risk therefor. Such a biomarker may be produced, released or otherwise generated in the body fluid or tissue. Typically, the presence, absence or abundance of the cancer biomarker according to the present invention is associated with at least one clinical parameter as referred to elsewhere herein, more preferably, with a change in a value for said at least one parameter. Preferably, said biomarker is selected from the group consisting of Prostate-specific antigen (PSA), CA125, CA19-9, carcinoembryonic antigen (CEA), Her2 / neu receptor, estrogen receptor (ER), progesterone receptor (PR), alpha fetoprotein (AFP), CAI 5-3, and prostate specific membrane antigen (PSMA). Moreover, the at least one clinical parameter in said case is, preferably, selected from the group consisting of: tissue image data, ultrasound data, glucose levels, and body mass index (BMI).

[0109] The term “PSA” as used herein, refers to prostate-specific antigen or kallikrein-3 (KLK3) encoded in humans by the KLK3 gene. PSA belongs to a subgroup of serine proteases having diverse physiological functions. It is secreted by the epithelial cells of the prostate gland in men and the para-urethral glands in women. Growing evidence suggests that many kallikreins are implicated in carcinogenesis and some have potential as novel cancer and other disease biomarkers. For PSA, there are five isoform known in humans (UniProt accession numbers P07288-1 to P07288-5). Several orthologues of PSA have been reported in various animal species.

[0110] The PSA referred to in accordance with the present invention is, preferably, human PSA having an amino acid sequence as deposited under UniProt accession number P07288. It will be understood that the term “PSA” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned PSA. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human PSA, preferably over the entire length of the said PSA, respectively.

[0111] The term “CA125” as used herein, refers to Mucin-16 also known as ovarian cancer-related tumor marker CA125 encoded in humans by the MUC16 gene. The encoded protein is a membrane-tethered mucin that contains an extracellular domain at its amino terminus, a large tandem repeat domain, and a transmembrane domain with a short cytoplasmic domain. This protein is thought to play a role in forming a barrier, protecting epithelial cells from pathogens. For CA125, there are five potential isoform known in humans (UniProt accession numbers A0AA34QW05, A0AA34QVW0, M0R2S7, M0R2Y5 and M0QZZ9). Several orthologues of CA125 have been reported in various animal species.

[0112] The CA125 referred to in accordance with the present invention is, preferably, human CA125 having an amino acid sequence as deposited under UniProt accession number Q8WXI7. It will be understood that the term “CA125” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned CA125. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human CA125, preferably over the entire length of the said CA125, respectively.

[0113] The term “CAI 9-9” as used herein, refers to the carbohydrate antigen 19-9, also known as sialyl-LewisA. It is a tetrasaccharide which is usually attached to O-glycans on the surface of cells. It is known to play a role in cell-to-cell recognition processes. It is also a tumor marker used primarily in the management of pancreatic cancer. The chemical formula of CA19-9 is C31H52N2O23.

[0114] The term “CEA” as used herein, refers to the carcinoembryonic antigen, a family of glycoproteins involved in cell adhesion. CEA is normally produced in gastrointestinal tissue during fetal development, but the production stops before birth. CEA are glycosyl phosphatidyl inositol (GPI) cell-surface-anchored glycoproteins whose specialized sialofucosylated glycoforms serve as functional colon carcinoma L-selectin and E-selectin ligands, which may be critical to the metastatic dissemination of colon carcinoma cells. Immunologically they are characterized as members of the CD66 cluster of differentiation. The proteins include CD66a, CD66b, CD66c, CD66d, CD66e, CD66f.

[0115] The CEA protein referred to in accordance with the present invention is, preferably, human CEA having an amino acid sequence as deposited under RCSB PDB accession number 1E07. It will be understood that the term “CEA” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned CEA. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human CEA, preferably over the entire length of the said CEA, respectively.

[0116] The term “Her2 / neu receptor” as used herein, refers to the human epidermal growth factor receptor 2, also known as ERBB2, encoded in humans by the ERBB2 gene. This gene encodes a member of the epidermal growth factor (EGF) receptor family of receptor tyrosine kinases which are part of several cell surface receptor complexes, butthat apparently need a co-receptor for ligand binding. ERBB2 regulates outgrowth and stabilization of peripheral microtubules and is involved in transcriptional regulation in the nucleus. For Her2 / neu, there are six isoforms known in humans (UniProt accession numbers P04626-1 to P04626-6). Several orthologues of Her2 / neu have been reported in various animal species.

[0117] The Her2 / neu receptor referred to in accordance with the present invention is, preferably, human Her2 / neu having an amino acid sequence as deposited under UniProt accession number P04626. It will be understood that the term “Her2 / neu receptor” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned Her2 / neu. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human Her2 / neu, preferably over the entire length of the said Her2 / neu, respectively.

[0118] The term “ER” as used herein, refers to estrogen receptors encoded in humans by the ESRI gene. ER belongs to a group of receptors that are activated by the hormone estrogen. Once activated by estrogen, the ER is able to translocate into the nucleus and bind to DNA to regulate the activity of different genes (i.e. it is a DNA-binding transcription factor). The hormones and their receptors are involved in the regulation of eukaryotic gene expression and affect cellular proliferation and differentiation in target tissues. There are two different forms of the estrogen receptor, i.e. estrogen receptor 1 (ER-alpha) and estrogen receptor 2 (ER-beta), each encoded by a separate gene, i.e. ESRI and ESR2, respectively. For ER-alpha, there are four isoforms known in humans (UniProt accession numbers P03372-1 to P03372-4). For ER-beta, there are nive isoforms known in humans (UniProt accession numbers Q92731-1 to Q92731-9). Several orthologues of ER-alpha and ER-beta have been reported in various animal species. The estrogen receptor referred to in accordance with the present invention is, preferably, human ER having an amino acid sequence as deposited under UniProt accession number P03372 (ER- alpha) or Q92731 (ER-beta). It will be understood that the term “ER” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned ER. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human ER, preferably over the entire length of the said ER, respectively.

[0119] The term “PR” as used herein, refers to progesterone receptors, also known as NR3C3, encoded in humans by the PGR gene. It is activated by the steroid hormone progesterone. The steroid hormones and their receptors are involved in the regulation of eukaryotic gene expression and affect cellular proliferation and differentiation in target tissues. Depending on the isoform, progesterone receptor functions as a transcriptional activator or repressor. For PR, there are five isoforms known in humans (UniProt accession numbers P06401-1 to P06401-5). Several orthologues of PR have been reported in various animal species.

[0120] The progesterone receptor referred to in accordance with the present invention is, preferably, human PR having an amino acid sequence as deposited under UniProt accession number P06401. It will be understood that the term “PR” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned PR. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human PR, preferably over the entire length of the said PR, respectively.

[0121] The term “AFP” as used herein, refers to the alpha-fetoprotein encoded in humans by the AFP gene. AFP is a major plasma protein produced by the yolk sac and the liver during fetal life. Alpha-fetoprotein expression in adults is often associated with hepatocarcinoma and with teratoma, and has prognostic value for managing advanced gastric cancer. For AFP, there is one potential isoform known in humans (UniProt accession numbers J3KMX3). Several orthologues of AFP have been reported in various animal species.

[0122] The AFP referred to in accordance with the present invention is, preferably, human AFP having an amino acid sequence as deposited under UniProt accession number P02771. It will be understood that the term “AFP” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned BRCA2. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human AFP, preferably over the entire length of the said AFP, respectively.

[0123] The term “CAI 5-3” as used herein, refers to the carcinoma antigen 15-3. It is a tumor marker for many types of cancer, most notably breast cancer. Its main use is for monitoring therapy in patients with metastatic disease.

[0124] The term “PSMA” as used herein, refers to the prostate-specific membrane antigen encoded in humans by the FOLH1 gene. This gene encodes a type II transmembrane glycoprotein belonging to the M28 peptidase family. The protein acts as a glutamate carboxypeptidase on different alternative substrates and is expressed in a number of tissues such as prostate, central and peripheral nervous system and kidney. It catalyses the hydrolysis of N- acetylaspartylglutamate (NAAG) to glutamate and N-acetylaspartate (NAA). For PSMA, there eight isoforms known in humans (UniProt accession numbers Q04609-1 to Q04609-8). Several orthologues of PSMA have been reported in various animal species.

[0125] The PSMA referred to in accordance with the present invention is, preferably, human PSMA having an amino acid sequence as deposited under UniProt accession number Q04609. It will be understood that the term “PSMA” also relates to variants of said proteins. Such variants have at least the same essential biological and immunological properties as the aforementioned PSMA. In particular, they share the same essential biological and immunological properties if they are detectable by the same specific assays referred to in this specification. Moreover, it is to be understood that a variant as referred to in accordance with the present invention shall have an amino acid sequence which differs due to at least one amino acid substitution, deletion and / or addition wherein the amino acid sequence of the variant is still, preferably, at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 97%, 98%, or 99% identical with the specific amino acid sequence of the human PSMA, preferably over the entire length of the said PSMA, respectively. The present invention also relates to a method for assessing a medical condition in a subject comprising the steps of: a) comparing the amount of at least one biomarker of interest for said medical condition to a reference, wherein said at least one biomarker has been determined in a sample of the subject; and b) assessing the medical condition in the subject based on the comparison made in step a) and improving the reliability of the said assessment by integrating at least one clinical parameter value of the medical condition obtained from a dataset of continuously determined clinical parameter values comprising the said at least one clinical parameter value into the biomarker-based assessment, wherein the sample and the at least one clinical parameter value have been obtained from the subject within a short time window, wherein said at least one biomarker is determined by using a point-of-care analytical device and / or wherein the dataset comprising the at least one clinical parameter is continuously determined by a wearable sensing device.

[0126] Preferably, said at least one clinical parameter value comprised in the dataset has been monitored continuously. Preferably, said method is a computer-implemented method. Preferably, all steps of the said computer-implemented method may be performed by one or more processing units of a computer or computer network. The values for the biomarker amount may be automatically uploaded from an point-of-care analyzing device, such as an POC IVD device, while the dataset for the clinical parameter can be automatically uploaded from a sensing wearable device. Alternatively, the data can be received by the processing unit by inputting the data manually via a user interface.

[0127] The present invention provides for a system for assessing a medical condition in a subject comprising: a) an analytical device for determining the amount of at least one biomarker for said medical condition in a sample of the subject; b) a sensing device for determining at least one clinical parameter, wherein said sensing device provides a dataset of continuously determined clinical parameter values from the subject comprising at least one clinical parameter value of the medical condition; c) an evaluation unit comprising a data processor adapted for i) comparing the amount of the at least one biomarker in the sample determined by the analytical device of a) to a reference and ii) assessing the medical condition by making a biomarker-based assessment thereof and integrating into said biomarker-based assessment the at least one clinical parameter value of the medical condition obtained from the dataset provided by the sensing device, whereby the assessment is improved.

[0128] The term “system” as used herein refers to a plurality of devices that are operatively linked to each other wherein said devices may be in physical proximity or may be apart and operate remote. Accordingly, the devices of the system may be operatively linked by wire if in physical proximity and may be, preferably, located in a single housing, or they may be linked by remote connections such as WiFi, WLAN, Bluetooth, cellular networks, radio waves, Internet, and the like. In the latter case, the devices of the system of the present invention, typically, comprise a transmitter for transmitting data and / or a receiver for receiving said data. The system according to the present invention shall comprise an analytical device, a sensing device and an evaluation unit. The analytical device and the sensing device shall submit data on the biomarker amount and clinical parameter value to the evaluation unit which is adapted to carry out the method of the invention and, thus, making the assessment of the medical condition.

[0129] The term “analytical device” as used herein refers to a device that is capable of determining the amount of the at least one biomarker in the sample of the subject. The analytical device, typically, comprises at least one detection zone being capable of detecting the biomarker present in the sample. The detector may also comprise a reaction zone that allows carrying out a chemical detection reaction. Preferably, prior to introducing the sample into the detection zone, the sample may be contacted to detection agents in order to generate detectable signals, e.g., by allowing the formation of specific complexes between the biomarker molecules and detection agents which specifically bind thereto. These complexes, typically, also comprise a detectable label that can be detected by the detector in the detection zone. The detection zone shall be adapted to determine the amount of the biomarkers based on the presence, absence or intensity of detectable signals generated. The determined amount can be subsequently transmitted to the evaluation unit for making the comparison to the reference, and, typically, also making the biomarker-based assessment.

[0130] Preferably, said analytical device is point-of-care analytical device. A point-of-care device is a device used at or near the site of patient care providing immediate results. Accordingly, fast clinical decisions may be made by the subject itself or by clinicians. These devices are designed for ease of use and rapid deployment in various settings, including hospitals, clinics, ambulances, homes, and remote locations. Preferably, the point-of-care analytical device is a device adapted for patient self-testing. The point-of-care analytical device according to the present invention, preferably, encompass means for rapid antigen testing. The term “sensing device” as used herein refers to a device which is capable of determining the at least one clinical parameter, preferably, in a non-invasive way. These devices typically incorporate advanced sensor technologies, e.g., optical, electrical, mechanical, or chemical sensors, signal processing capabilities, and wireless communication modules to ensure realtime or near-real-time data collection and transmission to external devices or cloud-based platforms for further analysis. The sensing device is, typically, a wearable device since it shall be used, preferably, to monitor the clinical parameter at the subject.

[0131] Thus, preferably, the sensing device is a wearable sensing device. A wearable sensing device for measuring clinical parameters refers to a compact, portable, and user-friendly electronic apparatus designed to be worn on the body, either as an accessory or integrated into clothing or other wearable items, that utilizes one or more sensors to continuously, intermittently or on demand monitor, record, and transmit data on various physiological and health-related metrics. The dataset comprising the data relating to the at least one clinical parameter can be transmitted to the evaluation unit, preferably, wirelessly via Bluetooth, WiFi, WLAN, or cellular networks. Typically, the wearable sensing device comprises user-friendly interfaces such as mobile applications or web portals for users to access, review, and share their health data.

[0132] The term “evaluation unit” as used herein refers to a device unit comprising a data processor adapted for i) comparing the amount of the at least one biomarker in the sample determined by the analytical device to a reference, thereby assessing the medical condition, and assessing the medical condition by making a biomarker-based assessment thereof and integrating into said biomarker-based assessment the at least one clinical parameter value of the medical condition obtained from the dataset provided by the sensing device, whereby the assessment is improved. The evaluation unit may also comprise permanent or temporary storage units for storing determined amounts for the biomarker, values for the clinical parameter and / or suitable references. The processor of the evaluation unit is adapted for carrying out the comparison of the determined amount of the biomarker in the sample and the reference. Moreover, the processors shall be adapted also for integrating into said biomarker-based assessment the at least one clinical parameter of the medical condition obtained from a dataset determined by the sensing device, whereby the assessment is improved. Typically, it may run one or more implemented algorithm for doing so. The processor, typically, comprises a Central Processing Unit (CPU) and / or one or more Graphics Processing Units (GPUs) and / or one or more Application Specific Integrated Circuits (ASICs) and / or one or more Tensor Processing Units (TPUs) and / or one or more field-programmable gate arrays (FPGAs) or the like. A processor may, for example, be or may be included in a general-purpose computer or a portable computing device. It should also be understood that multiple computing devices may be used together, e.g., over a network or other methods of transferring data, for per-forming one or more steps of the methods disclosed herein. Exemplary computing devices include desktop computers, laptop computers, personal data assistants (“PDA”), cellular devices, smart or mobile devices, tablet computers, servers, and the like. In general, a data processing element comprises a processor capable of executing a plurality of instructions (such as a program of software). The processor, typically, comprises or has access to a memory. The memory, typically, comprises ta stored reference to be used for the comparison. A memory is a computer readable medium and may comprise a single storage device or multiple storage devices, located either locally with the computing device or accessible to the computing device across a network, for example. Computer-readable media may be any available media that can be accessed by the computing device and includes both volatile and non-volatile media. Further, computer readable-media may be one or both of re-movable and non-removable media. By way of example, and not limitation, computer-readable media may comprise computer storage media. Exemplary computer storage media include RAM, ROM, EEPROM, flash memory or any other memory technology, CD-ROM, Digital Versatile Disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used for storing a plurality of instructions capable of being accessed by the computing device and executed by the processor of the computing device. The processor may also comprise or has access to an output device. Exemplary output devices include fax machines, displays, printers, and files, for example.

[0133] It will be understood that for the system of the invention, it is also, preferably, envisaged that the sample and the dataset comprising the at least one clinical parameter have been obtained from the subject within a short time window.

[0134] The present invention relates to a device comprising an evaluation unit comprising a data processor adapted for i) comparing the amount of the at least one biomarker of a medical condition in a sample determined by a analytical device to a reference, , and ii) assessing the medical condition by making a biomarker-based assessment thereof and integrating into said biomarker-based assessment the at least one clinical parameter value of the medical condition obtained from the dataset provided by the sensing device, whereby the assessment is improved.

[0135] Yet, the present invention relates, in general, to use of the amount of at least one biomarker of interest for said medical condition in a sample of the subject or a detection agent for said at least one biomarker for assessing a medical condition in a subject, wherein said assessment is to be improved by integrating at least one clinical parameter value of the medical condition obtained from a dataset of continuously determined clinical parameter values comprising the said at least one clinical parameter value into the biomarker-based assessment and wherein the sample and the dataset comprising the at least one clinical parameter have been obtained from the subject within a short time window.

[0136] The present invention, furthermore, relates, in general, to the use of a detection agent for the amount of at least one biomarker of interest for said medical condition in a sample of the subject or a detection agent for said at least one biomarker for assessing a medical condition in a subject, wherein said assessment is to be improved by integrating at least one clinical parameter value of the medical condition obtained from a dataset of continuously determined clinical parameter values comprising the said at least one clinical parameter value into the biomarker-based assessment and wherein the sample and the dataset comprising the at least one clinical parameter have been obtained from the subject within a short time window.

[0137] The following embodiments are particular preferred embodiments of the present invention:

[0138] Embodiment 1 : A computer-implemented method for assessing a medical condition in a subject comprising the steps of: a) determining the amount of at least one biomarker of interest for said medical condition in a sample of the subject; b) comparing the determined amount of the at least one biomarker to a reference; and c) assessing the medical condition in the subject based on the comparison made in step b) and improving the reliability of the said assessment by integrating at least one clinical parameter value of the medical condition obtained from a dataset of continuously determined clinical parameter values comprising the said at least one clinical parameter value into the biomarkerbased assessment, wherein the sample and the at least one clinical parameter value have been obtained from the subject within a short time window, wherein said at least one biomarker is determined by using a point-of-care analytical device and / or wherein the dataset comprising the at least one clinical parameter is continuously determined by a wearable sensing device.

[0139] Embodiment 2: The method of Embodiment 1, wherein said medical condition is a cardiovascular disease or disorder, preferably, myocardial infarction, heart failure, thrombosis, pulmonary embolism, clotting disorders, or atherosclerosis.

[0140] Embodiment 3 : The method of Embodiment 2, wherein said biomarker is a biomarker for a cardiovascular disease or disorder. Embodiment 4: The method of Embodiment 3, wherein said biomarker is selected from the group consisting of: a cardiac troponin, preferably, Troponin I or T, Creatine kinase MB (CK- MB), a brain natriuretic peptide, preferably, NT-proBNP, myoglobin, C-reactive protein (CRP), D-dimer, Fibrinogen and Lipoprotein associated phospholipase 2 (LP-PLA2).

[0141] Embodiment 5: The method of any one of Embodiments 2 to 4, wherein said at least one clinical parameter is selected from the group consisting of blood pressure, heart rate, electro cardiogram data, body mass index (BMI), smoking status, and alcohol consumption status, saturated blood oxygen, ankle or wrist swelling parameters (e.g., circumference and / or tissue elasticity of respective body parts and / or bioimpedance parameters and / or hydration levels), respiration rate, stroke volume, heart rate variability.

[0142] Embodiment 6: The method of Embodiment 1 , wherein said medical condition is a neuronal disease or disorder, preferably, neurodegenerative diseases, more preferably, Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, brain injury, stroke or multiple sclerosis.

[0143] Embodiment 7: The method of Embodiment 6, wherein said biomarker is a biomarker for a neuronal disease or disorder.

[0144] Embodiment 8: The method of Embodiment 7, wherein said biomarker is selected from the group consisting of Tau protein, beta-amyloid protein, Neurofilament protein, Glial fibrillary acidic protein (GFAP), Ubiquitin C-terminal hydrolase LI, SI 00 Calcium binding protein B, alpha Synuclein, Neuron-specific enolase, and Myelin basic protein (MBP).

[0145] Embodiment 9: The method of any one of Embodiments 6 to 8, wherein said at least one clinical parameter is selected from the group consisting of: cognitive assessment, motor function, gait and balance function, sensory function, reflex function, visual function, hearing, mood and behavior, electroencephalography, sleep function.

[0146] Embodiment 10: The method of Embodiment 1, wherein said medical condition is a metabolic disease or disorder, preferably, metabolic syndrome, diabetes, insulin resistance, dyslipidemia, hepatic disorders, hepatitis, non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH).

[0147] Embodiment 11 : The method of Embodiment 10, wherein said biomarker is a biomarker for a metabolic disease or disorder. Embodiment 12: The method of Embodiment 11, wherein said biomarker is selected from the group consisting of Insulin, Glucose Transporter 4 (GLUT4), adiponectin, leptin, Fatty acid binding protein 4, C-peptide, Glycated Hemoglobin (HbAlc), Hepatic Lipase (HL), Alanine Aminotransferase (ALT), and Aspartate Aminotransferase (ASZ).

[0148] Embodiment 13: The method of any one Embodiments 10 to 12, wherein said at least one clinical parameter is selected from the group consisting of: blood pressure, body mass index (BMI), and blood glucose levels.

[0149] Embodiment 14: The method of Embodiment 1, wherein said medical condition is cancer, preferably, prostate cancer, ovarian cancer, pancreatic cancer, colorectal cancer, breast cancer or hepatic cancer.

[0150] Embodiment 15: The method of Embodiment 14, wherein said biomarker is a biomarker for cancer.

[0151] Embodiment 16: The method of Embodiment 15, wherein said biomarker is selected from the group consisting of: Prostate-specific antigen (PSA), CA125, CA19-9, carcinoembryonic antigen (CEA), Her2 / neu receptor, estrogen receptor (ER), progesterone receptor (PR), alpha fetoprotein (AFP), CAI 5-3, and prostate specific membrane antigen (PSMA).

[0152] Embodiment 17: The method of any one of Embodiments 14 to 16, wherein said at least one clinical parameter is selected from the group consisting of: tissue image data, ultrasound data, glucose levels, and body mass index (BMI).

[0153] Embodiment 18: The method of any one of claims 1 to 17 wherein said integrating at least one further clinical parameter value obtained from the dataset into the biomarker-based assessment in step c) comprises: i) comparing the at least one clinical parameter value to a reference and assessing the subject based on the said comparison; and ii) comparing the assessment of the subject based on the at least one clinical parameter value of step i) to the biomarker-based assessment; and wherein the reliability of the assessment is improved if the result of the comparison of the assessment of the subject based on the at least one clinical parameter of step i) to the biomarkerbased assessment is that the assessments are essentially identical.

[0154] Embodiment 19: The method of any one of Embodiments 1 to 18, wherein said subject is a mammal, preferably, a human. Embodiment 20: The method of any one of Embodiments 1 to 19, wherein said sample is a body fluid sample, preferably, a blood sample, e.g., whole blood, serum or serum, a saliva sample, a cerebrospinal fluid sample, an urine sample, a tissue sample, an interstitial fluid sample or a sweat sample.

[0155] Embodiment 21 : The method of any one of Embodiments 1 to 20, wherein said comprises carrying out steps a) and b) at a first predefined time point and at a second predefined time point and wherein step c) of the method comprises assessing the medical condition in the subject based on the comparison made in step b) for the amounts of the first time point and the second time point as well as the at least one clinical parameter value of the medical condition obtained from a dataset of continuously determined clinical parameter values at the first time point and the second time point.

[0156] Embodiment 22. The method of Embodiment 21, wherein said method further comprises an autocorrelation analysis in step c).

[0157] Embodiment 23: A computer-implemented method for assessing a medical condition in a subject comprising the steps of: a) comparing the amount of at least one biomarker of interest for said medical condition to a reference, wherein said at least one biomarker has been determined in a sample of the subject; and b) assessing the medical condition in the subject based on the comparison made in step a) and improving the reliability of the said assessment by integrating at least one clinical parameter value of the medical condition obtained from a dataset of continuously determined clinical parameter values comprising the said at least one clinical parameter value into the biomarker-based assessment, wherein the sample and the at least one clinical parameter value have been obtained from the subject within a short time window, wherein said at least one biomarker is determined by using a point-of-care analytical device and / or wherein the dataset comprising the at least one clinical parameter is continuously determined by a wearable sensing device.

[0158] Embodiment 24: A system for assessing a medical condition in a subject comprising: a) an analytical device for determining the amount of at least one biomarker for said medical condition in a sample of the subject; b) a sensing device for determining at least one clinical parameter, wherein said sensing device provides a dataset of continuously determined clinical parameter values from the subject comprising at least one clinical parameter value of the medical condition; c) an evaluation unit comprising a data processor adapted for i) comparing the amount of the at least one biomarker in the sample determined by the analytical device of a) to a reference and ii) assessing the medical condition by making a biomarker-based assessment thereof and integrating into said biomarker-based assessment the at least one clinical parameter value of the medical condition obtained from the dataset provided by the sensing device, whereby the assessment is improved.

[0159] Embodiment 25: The system of Embodiment 24, wherein said analytical device is a point-of- care analytical device.

[0160] Embodiment 26: The system of Embodiment 24 or 25, wherein said sensing device is a wearable sensing sensor.

[0161] Embodiment 27: The system of any one of Embodiments 24 to 26, wherein said sample and said at least one clinical parameter value comprised by the dataset have been obtained from the subject within a short time window.

[0162] Embodiment 28: A device comprising an evaluation unit comprising a data processor adapted for i) comparing the amount of the at least one biomarker of a medical condition in a sample determined by an analytical device to a reference, and ii) assessing the medical condition by making a biomarker-based assessment thereof and integrating into said biomarker-based assessment the at least one clinical parameter value of the medical condition obtained from the dataset provided by the sensing device, whereby the assessment is improved.

[0163] Embodiment 29: Use of the amount of at least one biomarker of interest for said medical condition in a sample of the subject or a detection agent for said at least one biomarker for assessing a medical condition in a subject, wherein said assessment is to be improved by integrating at least one clinical parameter value of the medical condition obtained from a dataset of continuously determined clinical parameter values comprising the said at least one clinical parameter value into the biomarker-based assessment and wherein the sample and the dataset comprising the at least one clinical parameter have been obtained from the subject within a short time window.

[0164] Embodiment 30: Use of a detection agent for the amount of at least one biomarker of interest for said medical condition in a sample of the subject or a detection agent for said at least one biomarker for assessing a medical condition in a subject, wherein said assessment is to be improved by integrating at least one clinical parameter value of the medical condition obtained from a dataset of continuously determined clinical parameter values comprising the said at least one clinical parameter value into the biomarker-based assessment and wherein the sample and the dataset comprising the at least one clinical parameter have been obtained from the subject within a short time window. All references cited throughout this specification are herewith incorporated by reference with respect to the specifically mentioned disclosure content as well as in their entireties.

[0165] FIGURES

[0166] Figure: Schematic system: Combining Biomarker (BM) POC IVD testing results and Clinical Parameters (CP) received from wearable sensing device for remote patient monitoring (patient self-testing at home). In this example, a blood biomarker (e.g. NT-proBNP) result at a specific point in time may be close to a threshold or border of a reference range for assessing the medical condition of the patient. Based on such blood biomarker results close to the respective thresholds or range borders alone, the assessment of the medical condition of the patient may remain ambiguous. Such ambiguous results are shown in the grey marked time points A and B of the BM results timeline, where the respective BM results are very close to the upper limit of the reference range for this blood biomarker.. The additional clinical parameters (CP) obtained from the same patient within a short time window to the blood biomarker measurement may reduce this ambiguity of the blood biomarker assessment alone and thereby strengthen and improve the assessment of the medical condition of the patient. In the example shown in the Figure at timepoint A (left grey time range), the values of clinical parameters CPI , CP2 and CP3 are also within the respective reference ranges of these clinical parameters, making the assessment of medical condition of the patient (to be within the normal range for this medical condition) more reliable and less ambiguous. In the example shown in the Figure at timepoint B (right grey time range), the values of clinical parameters CPI and CP3 are above the respective reference ranges of these clinical parameters for this medical condition, making the assessment of medical condition of the patient based on the blood biomarker result alone (even if it is tightly inside the normal range for the BM) more ambiguous. In such a case, a warning or alert can be generated and presented to the patient that e.g. a further measurement of the blood biomarker should be performed and / or a healthcare professional should be informed.

[0167] EXAMPLES

[0168] The following Example shall merely illustrate the invention and shall, by no means, be construed in a limiting way.

[0169] Example 1: Integrated system for assessing a medical condition such as heart failure

[0170] An integrated system is provided consisting of a POC IVD device and a digital wearable device. The digital wearable device is capable of monitoring digital biomarkers and vital signs such as heart rate, blood pressure, blood oxygen saturation, ankle swelling, stroke volume, heart rate variability, breathing rate, activity, and sleep pattern in a non-invasive and continuous manner. Such a device can be worn on the wrist, ankle, chest, arms, finger, etc. and can support in providing important information related to the condition of a patient's heart. Suitable devices are known and commercially available.

[0171] The data of digital biomarkers and clinical parameters from a wearable are combined with the data of blood biomarker NT-proBNP obtained from a POC IVD device. Suitable POC IVD devices are known and commercially available as well. Upon integration of the clinical parameter(s) into biomarker-based assessments, central lab-like test-results can be generated with improved reliability of the assessments.

[0172] When patients record data from a POC IVD device and wearable device, the error in decision making arising from limitations of POC IVD blood test results can be circumvented. In situations where a POC IVD device fails to provide accurate data, additional input such as heart rate, blood pressure, blood oxygen saturation, change in ankle’s circumference (ankle swelling), stroke volume, heart rate variability, respiration rate, activity, etc. measured continuously from a non-invasive wearable device can at least particularly compensate for the error in results caused by the use of a mobile POC IVD device instead of a central lab analytical system, particularly if the POC IVD device is used by a patient itself, and can help healthcare professional to take necessary actions for managing the heart failure patients.

[0173] Thus, compared to a standalone POC IVD device an integrated system consisting of POC IVD device and digital wearable device can provide improved central lab-like results and can be used for efficient remote monitoring of patients. The patients can use the solution for selftesting at the comfort of their homes.

[0174] Example 2: Comprehensive continuous assessment

[0175] When performing IVD testing, discrete measurements of NT-proBNP or other cardiac parameters are carried out using blood samples that can be collected once daily, preferably in the morning before breakfast, as biomarker levels can fluctuate throughout the day. This timing helps standardize these measurements and minimize the influence of dietary factors. The frequency may be adjusted based on the physician's assessment of the patient's individual needs and depending on the stability of their condition.

[0176] An in-vivo patch could measure NT-proBNP in interstitial fluid at least twice daily, for example, at 8:00 AM and 8:00 PM. This would allow for tracking of potential diurnal variations and provide a more comprehensive picture of the biomarker's dynamics. The specific timing can be programmed based on a recommendation from a physician, depending on the patient's individual needs and the stability of their condition.

[0177] The clinical parameters will be monitored continuously via smart device such as a chest patch or a wrist monitor. Continuous recording of clinical parameters enables diverse analyses. This analysis can focus on data within a specific time window, such as the interval between the latest and preceding blood / interstitial fluid (ISF) analyses of the biomarker. Within this window, an algorithm identifies trends across the parameter dataset, considering not just individual changes but also combinations of parameters.

[0178] This analysis is then compared with biomarker measurement data for comprehensive assessment.

[0179] For carrying out the assessment, automated techniques like correlation analysis, regression analysis, hypothesis testing, and time series analysis, etc. are used to identify patterns, including anomalies, in clinical parameter datasets and correlate them with changes in the biomarker levels.

[0180] An example is autocorrelation (one of the methods for time series analysis) which can be performed as follows:

[0181] Autocorrelation analysis is one the key methods in time series analysis. In heart failure, the pattern of relevant clinical parameters, such as heart, blood pressure, SpO2, respiration rate, etc. is less predictable and more disorganized than in a subject not suffering from heart failure. A less structured pattern results in weaker correlations between current and past values, leading to lower autocorrelation values, which would then be an indication for a possible heart failure event.

[0182] When NT-proBNP is measured at time t from IVD or in-vivo sensor patch, autocorrelation analysis for vital signs such as heart rate, blood pressure, SpO2, respiration rate, heart rate variability, etc., at various time lags is performed: t vs t-30 min, t vs t-1 hour, t vs t-2 hours, t vs t-4 hours, ,.,t vs t-24 hours, wherein the last NT- proBNP value was measured at t-24 hours. For consistent high autocorrelation values, true NT- proBNP (t-24) value > or = true NT-proBNP (t) value, and for consistent low autocorrelation values, true NT-proBNP (t-24) value < true NT-proBNP (t) value.

[0183] A measurement is considered error-free if the autocorrelation values of the clinical parameters within the time windows from t to t-24h are consistent with the NT-proBNP values measured at both, t and t-24h, by the device. If any discrepancy exists, the device's display unit will show a measurement error code. Such type of analysis will aid in detecting potential measurement errors efficiently from an error-prone IVD POC device or in-vitro sensor patch.

Claims

1. Claims1. A computer-implemented method for assessing a medical condition in a subject comprising the steps of: a) determining the amount of at least one biomarker of interest for said medical condition in a sample of the subject; b) comparing the determined amount of the at least one biomarker to a reference; and c) assessing the medical condition in the subject based on the comparison made in step b) and improving the reliability of the said assessment by integrating at least one clinical parameter value of the medical condition obtained from a dataset of continuously determined clinical parameter values comprising the said at least one clinical parameter value into the biomarker-based assessment, wherein the sample and the at least one clinical parameter value have been obtained from the subject within a short time window, wherein said at least one biomarker is determined by using a point-of-care analytical device and / or wherein the dataset comprising the at least one clinical parameter is continuously determined by a wearable sensing device.

2. The method of claim 1, wherein said medical condition is a cardiovascular disease or disorder, preferably, myocardial infarction, heart failure, thrombosis, pulmonary embolism, clotting disorders, or atherosclerosis.

3. The method of claim 2, wherein said biomarker is a biomarker for a cardiovascular disease or disorder, preferably, selected from the group consisting of: a cardiac troponin, preferably, Troponin I or T, Creatine kinase MB (CK-MB), a Brain natriuretic peptides, preferably, NT-proBNP, myoglobin, C-reactive protein (CRP), D-dimer, Fibrinogen and Lipoprotein associated phospholipase 2 (LP-PLA2) and / or wherein said at least one clinical parameter is selected from the group consisting of: blood pressure, heart rate, electro cardiogram data, body mass index (BMI), smoking status, and alcohol consumption status, saturated blood oxygen, ankle or wrist swelling parameters (e.g. circumference and / or tissue elasticity of respective body parts and / or bioimpedance parameters and / or hydration levels), respiration rate, stroke volume, heart rate variability, thoracic impedance, echocardiography, cardiac output.

4. The method of claim 1, wherein said medical condition is a neuronal disease or disorder, preferably, neurodegenerative diseases, more preferably, Alzheimer's disease,Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, brain injury, stroke or multiple sclerosis.

5. The method of claim 4, wherein said biomarker is a biomarker for a neuronal disease or disorder, preferably, selected from the group consisting of Tau protein, beta-amyloid protein, Neurofilament protein, Glial fibrillary acidic protein (GFAP), Ubiquitin C- terminal hydrolase LI, SI 00 Calcium binding protein B, alpha Synuclein, Neuronspecific enolase, and Myelin basic protein (MBP) and / or wherein said at least one clinical parameter is selected from the group consisting of: cognitive assessment, motor function, gait and balance function, sensory function, reflex function, visual function, hearing, mood and behavior, electroencephalography, sleep function.

6. The method of claim 1, wherein said medical condition is a metabolic disease or disorder, preferably, metabolic syndrome, diabetes, insulin resistance, dyslipidemia, hepatic disorders, hepatitis, non-alcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH).

7. The method of claim 6, wherein said biomarker is a biomarker for a metabolic disease or disorder, preferably, selected from the group consisting of Insulin, Glucose Transporter 4 (GLUT4), adiponectin, leptin, Fatty acid binding protein 4, C-peptide, Glycated Hemoglobin (HbAlc), Hepatic Lipase (HL), Alanine Aminotransferase (ALT), and Aspartate Aminotransferase (ASZ) and / or wherein said at least one clinical parameter is selected from the group consisting of: blood pressure, body mass index (BMI), and blood glucose levels.

8. The method of claim 1, wherein said medical condition is cancer, preferably, prostate cancer, ovarian cancer, pancreatic cancer, colorectal cancer, breast cancer or hepatic cancer.

9. The method of claim 8, wherein said biomarker is a biomarker for cancer, preferably, selected from the group consisting of: Prostate-specific antigen (PSA), CA125, CA19- 9, carcinoembryonic antigen (CEA), Her2 / neu receptor, estrogen receptor (ER), progesterone receptor (PR), BRACA1, BRACA2, alpha fetoprotein (AFP), CAI 5-3, and prostate specific membrane antigen (PSMA) and / or wherein said at least one clinical parameter is selected from the group consisting of: tissue image data, ultrasound data, glucose levels, and body mass index (BMI).

10. The method of any one of claims 1 to 9 wherein said integrating at least one further clinical parameter value obtained from thedataset into the biomarker-based assessment in step c) comprises: i) comparing the at least one clinical parameter value to a reference and assessing the subject based on the said comparison; and ii) comparing the assessment of the subject based on the at least one clinical parameter value of step i) to the biomarker-based assessment; and wherein the reliability of the assessment is improved if the result of the comparison of the assessment of the subject based on the at least one clinical parameter of step i) to the biomarker-based assessment is that the assessments are essentially identical.

11. The method of any one of claims 1 to 10, wherein said comprises carrying out steps a) and b) at a first predefined time point and at a second predefined time point and wherein step c) of the method comprises assessing the medical condition in the subject based on the comparison made in step b) for the amounts of the first time point and the second time point as well as the at least one clinical parameter value of the medical condition obtained from a dataset of continuously determined clinical parameter values at the first time point and the second time point.

12. The method of claim 11, wherein said method further comprises an autocorrelation analysis in step c).

13. A system for assessing a medical condition in a subject comprising: a) an analytical device for determining the amount of at least one biomarker for said medical condition in a sample of the subject; b) a sensing device for determining at least one clinical parameter, wherein said sensing device provides a dataset of continuously determined clinical parameter values from the subject comprising at least one clinical parameter value of the medical condition; c) an evaluation unit comprising a data processor adapted for i) comparing the amount of the at least one biomarker in the sample determined by the analytical device of a) to a reference and ii) assessing the medical condition by making a biomarker-based assessment thereof and integrating into said biomarker-based assessment the at least one clinical parameter value of the medical condition obtained from the dataset provided by the sensing device, whereby the assessment is improved.

14. The system of claim 13, wherein said analytical device is a point-of-care analytical device and / or wherein said sensing device is a wearable sensing sensor.

15. The system of claim 13 or 14, wherein said sample and said at least one clinical parameter value comprised by the dataset have been obtained from the subject within a short time window.

16. Use of the amount of at least one biomarker of interest for said medical condition in a sample of the subject or a detection agent for said at least one biomarker for assessing a medical condition in a subject, wherein said assessment is to be improved by integrating at least one clinical parameter value of the medical condition obtained from a dataset of continuously determined clinical parameter values comprising the said at least one clinical parameter value into the biomarker-based assessment and wherein the sample and the dataset comprising the at least one clinical parameter have been obtained from the subject within a short time window.

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